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Mobility-as-a-Service and changes in travel preferences and travel behaviour: a literature review

  • KiM Netherlands Institute for Transport Policy Analysis

Abstract and Figures

Mobility-as-a-Service (MaaS), a transport concept integrating various mobility services into one single digital platform, elicits high expectations as a means of providing customised door-to-door transport solutions. To date, the frequent claims about the positive contributions MaaS will make towards achieving sustainability goals rely on a scattering of limited yet insightful research findings. Many research questions remain unanswered, however. Are people willing to accept MaaS as a new transport service (on a daily basis)? The KiM Netherlands Institute for Transport Policy Analysis looked for answers by means of an extensive research program. In the initial exploratory phase of the research, KiM conducted an extensive literature review. The findings are presented in the report, ‘Mobility-as-a-Service and changes in travel preferences and travel behaviour: a literature review’.
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KiM Netherlands Institute for Transport Policy Analysis
Mobility-as-a-Service and changes
in travel preferences and travel
behaviour: a literature review
Anne Durand, Lucas Harms, Sascha Hoogendoorn-Lanser, Toon Zijlstra
Summary 3
1 Introduction 6
1.1 Problem statement 6
1.2 Goal, research question and relevance of the study 6
1.3 Approach 7
1.4 Denitionsandscope 8
1.5 Structure of the report 9
2 DeningMaaS 10
2.1 MaaS and forms of integration 10
2.2 A topology for MaaS and “MaaS schemes” 10
2.3 Shared mobility modes 11
2.4 Presentation of MaaS schemes 12
3 Lessonslearntoninuencingtravelpreferencesandbehaviour 14
3.1 The challenge of changing travel behaviour 15
3.2 Mobility integration, travel behaviour and preferences 16
3.3 Changing travel behaviour through mobile applications 19
3.4 Shared mobility modes, travel behaviour and preferences 20
3.5 Conclusion 26
4 SystematicliteraturereviewofthepotentialimpactofMaaSontravelpreferencesand
behaviour 27
4.1 Presentationoftheselectedpapersandtheassociatedresearchmethods 27
4.2 A change in the private car ownership paradigm? 31
4.3 PreconditionsinMaaS:theneedforautonomy,exibilityandreliability 32
4.4 Aspects adding value in MaaS 33
4.5 The user-side design of MaaS 35
4.6 Costs and willingness to pay 35
4.7 The importance of travellers’ characteristics 36
4.8 Conclusion 37
5 Conclusionandagendaforfurtherresearch 39
5.1 Conclusion 39
5.2 MaaS research agenda 41
Literature 42
AppendixA 52
AppendixB 54
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 2
Mobility-as-a-Service in 2018: high expectations and fragmented insights
Integrated and seamless mobility has been a futuristic vision of mobility (in urban regions mainly) for a few
years already. Today, Mobility-as-a-Service(MaaS) embodies that vision. It is a new transport concept that
door transport and offering personalised trip planning and payment options. Instead of owning individual
modes of transportation, or to complement them, customers would purchase mobility service packages
tailored to their individual needs, or simply pay per trip. Although MaaS is a relatively new concept, many
studies, technical reports and business cases related to MaaS have appeared over the past couple of years.
Explorative and systematic literature reviews on MaaS, travel behaviour and preferences
In times when many see in MaaS a tool for instigating more sustainable travel behaviour patterns among
the population, it is relevant to establish whatwecurrentlyknow,basedonscienticliterature,about
MaaS’spotentialimpactsontravelpreferencesandtravelbehaviour. Two complementary pathways
on travel preferences and behaviour outside of MaaS. Indeed, there is already a considerable amount of
studies that provide relevant insights to understand the potential impact of MaaS on travellers. Second, we
conducted a systematic literature review focused exclusively on MaaS, travel preferences and travel behaviour.
This systematic review provides structured knowledge about the state-of-the-art research on MaaS and
travel behaviour and preferences. The main insights gained from these reviews are summarised below.
Uncertainties around changes in travel behaviour
Generally, the reviewed studies show that MaaS has the potential to reach certain travellers, to support
decreases in private car use and to instigate different travel patterns among these travellers. However, the
impactmagnitude, the timeline and direction of these changes remain relatively uncertain and require
more quantitative results, whether on the individual level (travel behaviour, travel preferences) or societal
level (e.g. social and environmental sustainability). Nevertheless, it is unlikely that a drastic shift from the
private car ownership paradigm to the MaaS paradigm will occur within a few years.
Current literature can however inform us about the preconditions for adopting MaaS and for subsequent
changes in travel behaviour patterns, while also providing qualitative indications of potential users
and impacts.
Preconditions for adoption of MaaS
incidental trips; however, to allow such trips to occur even incidentally, individuals must actually start using
MaaS. The adoption of MaaS, conditioning a subsequent potential change in travel behaviour, is likely to
require a combination of multiple aspects. First, it is important that MaaSaddsenoughvaluefortravellers.
MaaS pilots show that choice freedom, tailor-made offers and increases in travel convenience – notably
through high levels of integration – can positively impact MaaS adoption. The need for such “tailor-made
all-inclusiveness” is especially valid if the asking price is higher than what travellers are used to. This leads
to the second point about costs: to provide travellers with a viable, lasting alternative, adopting the service
must be economically feasible. In that sense, customising the type of offer to the user will likely play a
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 3
key role. Adopting the service must also be perceivedaseconomicallyfeasible;forexample,theprice
structure of MaaS could be an obstacle, especially for car owners. Consequently, the latter might need
to be introduced to MaaS in a different manner than non-car-owners. Third, it is crucial that MaaSdoes
Being able to combine modes during a trip is deemed a key strength of MaaS. Shared mobility modes in
particular (car sharing, bike sharing, individual and collective demand-responsive transport) can provide
raises questions about reliability. Fourth, a particularly crucial point isasmartdesignoftheMaaSuser
interface, rendering it accessible for everyone.
Preconditions for MaaS’s potential to challenge travel behaviour patterns
In order to have a chance to instigate new travel behaviour patterns, it is likely that the MaaS user
interface (e.g. a smartphone application) needs to include behaviouralchangesupportsystems
features. There are four of these: customisation to the user, information and feedback, commitment,
and an appealing and simple design. However, these features may not be sufcient conditions for
(2) ticketing and payment integration, (3) service integration, and (4) integration of societal goals.
Research reveals that a comprehensive approach combining multiple levels of integration is more likely
toencouragepassengerstousetheintegratedmodes than solely a lower level of integration. Further,
bundles as having the potential to alter the way people perceive travel alternatives rather than physically
altering alternatives, thereby potentiallypromotingtheusemoresustainablemodes, and notably
shared mobility modes. The latter have proven to be effective for decreasingcaruse and, to a lesser
Potential MaaS users
to MaaS from a more traditional mobility paradigm. Current literature only provides very limited
quantiedindicationsaboutwhothesetravellersare,andnoquanticationaboutthe extenttowhich
changes in travel behaviour among the wider population remains uncertain. Skills, values (like a low
sense of ownership), age and place of residence, and other socioeconomic, sociodemographic and
cultural characteristics are likely to play roles in the adoption of MaaS and potential subsequent changes
in travel behaviour.
Impacts of MaaS
This study names a few impacts that MaaS could have. In particular, we note that the question of who
MaaS will reach raises questions that only a few studies have addressed: namely, MaaS’s impact on
(perceived) accesstotransportand social inclusion. In addition to this, MaaS could impact a wide
range of dimensions through the changes in travel behaviour it could trigger, including environmental
sustainability (e.g. air pollution, noise pollution) and thetransportsystem generally (e.g. capacity
optimisation, passenger demand). However, at such a preliminary stage in this new type of paradigm,
impact on sustainability via car use: while MaaS’s access-based paradigm may compel decreases in
private car use, it may also provide access to motorised vehicles to people who previously did not have
such access.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 4
Research agenda
decisions within MaaS, especially on the quantitative side, is needed in order to be able to make more
conclusive statements about MaaS adoption and travel behaviour changes. Secondly, in order to build a
solid base of evidence, more MaaS pilots with a systematic impact assessment available to the general
based system, but still many doubts about their reliability, impact and synergy. More research on these
topics is desired.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 5
1 Introduction
Integrated and seamless mobility has been a futuristic vision of mobility (in urban regions mainly) for a
few years now (Loose, 2010; Motta et al., 2013; Preston, 2012; Schade et al., 2014). Today, Mobility-as-
a-Service (MaaS)1embodiesthatvision.MaaSisanewtransportconceptthatintegratesexistingand
new mobility services into one single digital platform, providing customised door-to-door transport
and offering personalised trip planning and payment options. Instead of owning individual modes of
transportation, or to complement individual modes of transport, customers would purchase mobility
service packages2 tailored to their individual needs, or simply pay per trip for customised travel options.
1.1 Problem statement
Although MaaS is a relatively new concept, many studies, technical reports, opinion pieces and business
cases related to MaaS have appeared over the past couple of years. Indeed, numerous promises and
challenges emerge with the concept. According to Matyas and Kamargianni (2017), MaaS, when
demand management tool for assisting the shift towards more sustainable travel. The design question is
therefore important (Karlsson et al., 2016) and intrinsically linked to potential MaaS users. In fact, MaaS
is described in literature as a user-centric paradigm (Giesecke et al., 2016; Jittrapirom et al., 2017).
rapidly gone from nowhere to nearly everywhere in the personal transport sector” since 2014. In June
(Scopus) and found 37 peer-reviewed journal and conference papers mentioning the term in either
their titles, abstracts or keywords. By June 2018 this number had more than doubled to 76 citations.
challenges (ecosystem, technologies, integration of modes), rather than using in-depth analysis to
quantify how MaaS may impact travel preferences and behaviour, as already emphasised by Matyas
and Kamargianni (2017). Although multiple pilots and schemes have been initiated around the world
in recent years (see section 2.4),empiricalknowledgeofMaaS’sexpectedimpactsonpeople’stravel
preferences and travel behaviour remains limited, as highlighted by Ho et al. (2017). Consequently, the
frequent claims about the positive contributions MaaS will make towards achieving sustainability goals
1.2 Goal, research question and relevance of the study
Against this background, this study strives to respond to the “lack of clarity” about MaaS’s impacts on
travel behaviour and preferences, as stated by Wong (2017). The purpose of this research is therefore to
provide a better understanding of the ways in which MaaS might impact people’s travel preferences and
travel behaviour. The research question that this study seeks to answer is the following:
What can current literature teach us about the expected impacts of Mobility-as-a-Service (MaaS) on people’s travel
preferences and travel behaviour?
1 Also called Transportation-as-a-Service (TaaS) in the United States (Wong, 2017).
2 “Bundle”and“package”willbeusedinterchangeablyinthisstudy;foradenition,seesection2.1.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 6
Reviewing the potential impacts of MaaS on travel preferences and behaviour is relevant from the
research, business and policy perspectives, as it can inform various parties about the state of the research
pertaining to MaaS and travel behaviour. In this sense, the review helps discern what people would value
in such a new service and what might pose challenges, thereby providing a more nuanced yet realistic
picture of what MaaS can achieve for travellers and society in the near future. This study can be useful
to transport operators and authorities seeking to apply an attractively designed MaaS scheme. Further,
researchers may be interested in the research gaps found in this review.
1.3 Approach
research topics not directly focused on MaaS, but which are particularly relevant for MaaS. Second, we
conduct a systematic literature review of studies focused on MaaS and travel behaviour.
1.3.1 Explorative literature review of MaaS-related topics
on MaaS, such research is undeniably relevant to better understand the potential impact of Mobility-as-
a-Service on travel behaviour and preferences. These nine core characteristics (presented in no particular
hierarchical order) are:
1 The integration of transport modes, including shared mobility modes3(seedenitioninsection2.3)
and more traditional modes,
2 The tariff option (i.e. pay-as-you-go and mobility packages),
3 A single platform, where users can plan, book, pay and get tickets for their trips,
4 Multiple actors (customers, providers, platform owners, authorities, etc.),
5 The use of technologies (smartphones, Internet networks, ICT, etc.),
6 Demand orientation,
7 Registration requirement, to facilitate the use of the service and allow for customisation,
8 Personalisation to the needs of the user,
9 Customisation, enabling the user to modify the offered option based on their preferences.
The characteristics can be translated into relevant research themes pertaining to travel preferences and
travel behaviour. Based on the list of Jittrapirom et al. (2017), we selected three relevant research themes
The three chosen research themes are:
Mobility integration, travel behaviour and travel preferences,
ICT, particularly smartphone applications, and travel behaviour,
Shared mobility modes, travel behaviour and travel preferences
themes with literature that does necessarily pertain to MaaS yet is highly pertinent for MaaS.
manageable, no systematic paper selection criteria will be applied.
3 FollowingtheterminologydenedinShaheenetal.(2015),modeslikebikesharing,carsharingandon-demandmodesare
grouped under the term of shared mobility modes.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 7
1.3.2 Systematic literature review of MaaS and travel behaviour
At the time of writing, early 2018, there is a growing body of relevant studies on Mobility-as-a-Service
and travel behaviour and preferences (notions of travel preferences and behaviour, and especially their
connections,aredenedinsection1.4.1). We conduct a systematic literature review on Mobility-as-a-
First, there are studies based on MaaS pilots: UbiGo (Karlsson et al. (2016); Sochor et al. (2015); Sochor
et al. (2016); Strömberg et al. (2016); Strömberg et al. (2018); and Smile (Smile mobility, 2015)).
The study of Karlsson et al. (2017) was also selected, as it provided in-depth analysis of both pilots.
Second, there are studies that investigated the prospects for people to adopt MaaS and/or travellers’
decisions in MaaS through surveys and interviews (Alonso-González et al. (2017); Ho et al. (2017);
Haahtela and Viitamo (2017); Kamargianni et al. (2018); Matyas and Kamargianni (2018); Ratilainen
(2017); G. Smith et al. (2018)).
This systematic review allows us to devise a list of aspects that play or could play a role in the adoption of
MaaS and/or in changes in travel behaviour.
1.3.3 Schematic overview
systematic literature review. This approach is depicted in Figure 1.
 Figure1 The study’s two-step approach.
Selection of the relevant
themes for travel behaviour/
preferences and MaaS Explorativeliterature
review on these
3themes Expectedimpacts
Systematic selection of
studies on travel behaviour/
preferences and MaaS
Systematic literature
review on travel
and MaaS
in this study
1.4 Denitions and scope
our research.
1.4.1 Travel behaviour, travel preferences and their connection
Travel behaviour refers to how people move over space, how and why they travel from point A to
B, and how they use transport. In contrast, travel preferences refer to how people would prefer to
move over space. In this sense, travel behaviour is usually more constrained than travel preferences
(Kattiyapornpong & Miller, 2007). Intuitively, travel preferences can be understood as somehow
transportusersinuencedtheirtravelbehaviourthroughcontrolbeliefs4, under the constraints
of resources (e.g. time, money, skills). Although we acknowledge that the preferences–behaviour
our study.
4 Personalcontrolbeliefsreectthebeliefsofanindividualregardingtheextenttowhichtheyareabletoinuenceorcontrol
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 8
1.4.2 The sharing economy and consumer-to-consumer initiatives
The rise of MaaS is often associated with the emergence of the sharing economy, at least outside
argue that it only includes consumer-to-consumer (C2C) interactions (Frenken & Schor, 2017), others
carpooling or hitchhiking, which have been associated with the sharing economy for more than a
decade now (Benkler, 2004). Although Holmberg et al. (2016) incorporate peer-to-peer services in
to-consumer initiatives are included, nor empirical studies where such initiatives are considered (yet).
To avoid any ambiguity, we leave the notion of the sharing economy, and in particular C2C initiatives,
outside the scope of our study. Note however that we do not imply that MaaS and consumer-to-
consumer initiatives are incompatible.
1.4.3 Scope
We restrict our research scope to Mobility-as-a-Service and impacts on potential users (preferences,
(congestion, crowding in public transport, etc.), but rather merely as a consequence of impacts on
travellers; for more details, see Hensher (2018) (MaaS and road congestion), Hensher (2017) (MaaS
and bus contracts), Rantasila (2015) (MaaS and land use). Similarly, considerations on sustainability5
from our scope considerations on business models (see Aapaoja et al. (2017) and Sarasini et al.
(2017)), institutional conditions (see Mukhtar-Landgren et al. (2016)), information services, car market
from the scope of this study, as are Autonomous Vehicles (AVs), because MaaS must also be considered in
the absence of AVs (Hensher, 2018); see Kamargianni et al. (2018) for MaaS scenarios for the AV era.
1.5 Structure of the report
denitionofMaaS.Sections3and4followtheapproachdescribedinFigure 1,rstwiththeexplorative
literature review and second with the systematic literature review. Section 5 is the conclusion,
and travel behaviour and preferences.
5 Denitionsofsustainabilityvaryinliterature.Itisusuallyconsideredasencompassingsocial,economicandenvironmental
dimensions. Note though that in transport studies, sustainability is often considered from the environmental perspective
only, i.e. minimising car travel or the emission of air pollutants. Unsustainable transport is generally equated with car use
(Sunio & Schmöcker, 2017).
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 9
2 DeningMaaS
Multiple MaaS initiatives have emerged around the world in recent years since the early description by
Hietanen (2014): MaaS is “a mobility distribution model in which a customer’s major transportation
needs are met over one interface and are offered by a service provider”. As presented in section 1.3.1,
components. However, according to Sochor et al. (2017), the lack of characterisation of MaaS embracing
transition towards a MaaS-based transport system challenging. In this section we begin by introducing
presentation of MaaS schemes.
2.1 MaaS and forms of integration
Mobility-as-a-Service is frequently described in terms of integration (Hietanen (2014), Kamargianni
et al. (2015), Kamargianni et al. (2016), König et al. (2016), Sochor et al. (2017), and Jittrapirom et al.
two MaaS literature reviews, MaaS can comprise the following types of integration: payment, ticketing,
bundles, information and service 6 (Kamargianni et al., 2016; Sochor et al., 2017). Payment and ticketing
and service integration. What is new compared to the traditional concept of mobility integration is
bundle integration.
What is a bundle?WhenauserbuysamobilitypackageorbundleinthecontextofMaaS,theypre-
in time, distance or money units, with pre-determined service level agreements. Packages would have a
Internet connection and silent spaces in public transport, free snacks, etc. (Hietanen, 2014).
2.2 A topology for MaaS and “MaaS schemes”
Sochor et al. (2017) proposed a topology of MaaS, as shown in Figure 2, which they argue can facilitate
discussions about MaaS, notably “comparisons of” different schemes, as well as understanding the
section 3.2.1). We will use this scale in the remainder of this study. Note that a similar topology was
applied in the White Paper for the Dutch Ministry of Infrastructure and Water Management (MuConsult,
2017). The levels in Figure 2 are not necessarily dependent on each other, as UbiGo reached Level 3
arise, and some schemes may only achieve partial integration of a given level. In Figure 2, societal goals
refer to the integration of wider goals such as congestion mitigation and urban planning (see section 3.2
on mobility integration).
6 Information and service integration are also sometimes referred to as ICT and organisational integration in literature.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 10
Nowadays many mobility initiatives are labelled as MaaS, yet such initiatives only provide travel
information and no option to book or pay for any ticket: this is Level 1 of integration. In the remainder
of this study we use the term “MaaS schemes” to denote initiatives that reached at least Level 2 of the
typology in Figure 2. In such initiatives, users can at least book their tickets or pay for them via a single
platform, where information is most of the time also provided. Multiple initiatives at this stage are
König et al. (2016) and Sochor et al. (2017), amongst others). Note that this distinction is meant to
help keep our research efforts manageable and focused on initiatives with more advanced levels
of integration.
 Figure2 ProposedtopologyofMobility-as-a-Serviceincludinglevels(left)andexamples(right)(fromSochoretal.(2017)).
Policies, incentives, etc.
Bundling/subscription, contracts, etc.
Multimodal travel planner, price information
Before presenting MaaS schemes and classifying them according to the typology presented in Figure 2,
2.3 Shared mobility modes
Bike and car sharing are often included within MaaS schemes (see section 2.4). Bikesharing systems
allow users to pay to borrow shared bicycles for a short term from an unattended bike sharing station
systems have appeared, whereby users can pick up and drop off borrowed bikes at locations of their
sharing include the PT-bike (in the Netherlands), Citi Bikes (New York), Santander Cycles (London), and
free-oatingbikes,suchasFlickbike,Gobike,oBikeandMobike.Carsharing works similarly: once
subscribed to a service, people may borrow cars on a short-term basis (ranging from a few minutes
to a few days). There is a difference between one-way shared cars and return-to-base shared cars
in the world), Zipcar and GoGet (Australia), and cambio CarSharing (Germany and Belgium). Demand-
responsive forms of transport are sometimes offered within MaaS schemes or will soon be (see section
2.4);theyexistmainlyintwoforms.First,collectivedemand-responsivetransport (often abbreviated
as DRT) services are door-to-door or stop-to-stop services that provide casual, on-demand transport.
London, and UberPOOL in multiple countries. Second, there is individual demand-responsive transport,
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 11
frequently called ride hailing or ride-sourcing7. Companies offering such services are often referred to
as Transportation Network Companies (TNC’s). Ride-sourcing matches supply and demand by allowing
travellers to use a smartphone application to request individual car rides in real-time from potential
integrated in any MaaS scheme, although there are signs of initiatives in this direction (e.g. MaaS Alliance
2.4 Presentation of MaaS schemes
Multiple schemes have reached Level 2, although ticketing and payment are not necessarily integrated
yet. Payment integration only means that while a well-developed integrated platform may be available,
the associated journey planner does not display combinations of options, such as car sharing + train,
in Germany, myCicero in Italy, Tuup in Finland, NaviGoGo in Scotland and iDPASS in France. Ticketing
integration only means that separate fees must be paid to the various services, although the traveller has
a single ticket (e.g. smart card) for accessing all the various services. Often, partial payment integration is
provided through subscriptions and pay-per-use systems, as is the case for Hannovermobil in Germany,
in the Netherlands, employers provide employees with customisable business cards offering access
to public transport (PT) in the country, bike sharing and sometimes additional services. However, this
scheme provides only partial Level 1 integration, as no dedicated trip planner is yet available.
The Austrian pilot project Smile is a well-known MaaS scheme with Level 2 integration. This scheme
other parties, such as software engineers and environmental protection groups. The Smile app provided
multimodal routing (capable of combining private vehicles, PT and shared mobility modes within the
same trip), integrated payment and ticketing. As a follow-up to Smile, an improved trip planner was
developed (Beam-Beta), and together they gave birth to the WienMobil Lab app, operational since 2017.
was never operational: it would have integrated a variety of services, including bike sharing, car sharing,
The second scheme, UbiGo, was a Swedish pilot in which households chose prepaid bundles based on
their own needs; they would therefore plan their trips while taking into account the chosen bundle.
When the subscription ran out, because for instance someone had used all the available car rental days, it
was still possible to make trips using all modes, but they would be billed for them afterwards. A relaunch
initiative, which has been operational since 2016. At the time of writing, users can choose between two
types of bundles, in addition to pay-as-you-go: “Whim Urban”, costing €49 per month and offering
per month and presenting itself as a “Modern alternative for owning a car. At the price of owning a car you get
unlimited access to public transport, taxi or a [shared] car according to your daily need.” (MaaS Global, 2018).
Table 1 summarises MaaS initiatives around the world and the type of integration. Note that this
overview is not comprehensive, and that many initiatives are currently being developed or are deemed
Global, 2016).
7 This mode of transport is also sometimes called ride sharing, but this is inaccurate (Frenken & Schor, 2017).
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 12
 Table1 Overview of MaaS initiatives and description of the type of mobility integration.
Nameoftheinitiative Place Status Modes Typeof
moovel Hamburg and
Operational (2015-) Carsharing,taxi,urbanPT,
regional PT.
Level 2 (partial,
myCicero Italy Operational (2015-) Urban PT, regional PT,
international PT, parking,
permit for urban congestion
charging zones.
Level 2 (partial,
NaviGoGo Dundee and North
Scotland, UK
Operational (2017-) Carsharing,taxi,urbanPT,
regional PT.
Level 2 (partial,
iDPASS France Operational (2017-) Carrenting,taxi,valet
Level 2 (partial,
Tuup Turku region,
Operational (2016-) Car sharing, bike sharing,
Level 2 (partial,
integration to
come in 2018).
Hannovermobil Hannover,
Operational (2014-) Carsharing,taxi,urbanPT,
regional PT.
Level 2.
EMMA(TaM) Montpellier,
Operational (2014-) Bike sharing, car sharing,
urban PT, parking.
Level 2.
Business travellers
cards: NS Business Card,
Total Mobility, etc.
The Netherlands Operational
(national coverage
of these cards since
(Car sharing, parking, tank
urban PT, regional PT.
Level 2
(Business to
partial Level 1.
Smile Vienna, Austria Pilot (2014-2015) Bike sharing, car sharing,
Level 2.
WienMobil Lab Vienna, Austria Operational (2017-) Bike sharing, car sharing,
Level 2.
SHIFT Las Vegas, USA Planned (2013-
Bike sharing, car sharing,
Level 3.
UbiGo Gothenburg,
Pilot (2013-2014),
version 2.0 in
Bike sharing, car sharing, car
Level 3.
Whim Helsinki, Finland Operational (2016-) Bike sharing (car sharing to
urban PT, regional PT.
Level 3.
moovel was initiated and is fully owned by an industrial group, Daimler AG (Daimler AG, n.d.). Smile was
initiated by the infrastructure manager of the city of Vienna and was essentially a collaboration between
Vienna’s PT provider and Austria’s train operator (Smile mobility, 2015). NaviGoGo emerged as part
of a project that included Scottish governmental entities, ICT and mobility companies, and transport
unclear though. More research is needed in this area, but this is beyond the scope of our study.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 13
3 Lessons learnt on
preferences and
behaviour, according to pertinent research into travel preferences and travel behaviour conducted
outside of MaaS. Based on Jittrapirom et al. (2017), three relevant themes were selected (see section
Mobility integration, travel behaviour and preferences,
ICT, particularly smartphone applications, and travel behaviour,
Shared mobility modes, travel behaviour and preferences.
(2017), a concept close to MaaS arguably lies at their intersection, as depicted in Figure 3. Further, the
 Figure3 Thethreethemesdiscussedinthisexplorativeliteraturereviewandtheirintersections.
close to
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 14
3.1 The challenge of changing travel behaviour
This section describes why changing travel behaviour is challenging. Opportunities to challenge travel
behaviour are also highlighted.
3.1.1 Travel behaviour inertia
It has commonly been noted that travel behaviour tends to repeat itself not only on a daily basis,
but also on a weekly and perhaps even yearly basis (Pendyala et al., 2001). A stream of studies based
on motivational models (see Theory of Planned Behaviour by Ajzen (1991)) suggests that travellers’
behaviour is the result of a deliberation process (Bamberg et al., 2003; Bamberg & Schmidt, 2003), yet
such models neglect the repetitive nature of travel behaviour decisions (Gardner, 2009), which led to
The habit approach implies that there is little to no deliberation in the travel behaviour. In such cases,
risk and if the quality of the travel alternatives is only revealed upon use. According to Bovy and Stern
(1990), inertia is characterised by “certain thresholds that need to be crossed before changing routine
behaviour” (p. 32), “factors […] which encourage keeping the status quo and oppose behavioural change”
public transport travel time. However, informing such travellers of the travel time they can gain when
roles in travel behaviour, even more so than instrumental factors in some instances (e.g. leisure trips; see
Anable and Gatersleben (2005)). Note that research has shown that a mode shift behaviour is more likely
for leisure trips than work trips (Vedagiri & Arasan, 2009).
3.1.2 Questioning ownership?
Mobility in the 20th century was characterised by the arrival and reign of the car (Goodall et al., 2017).
their own cars (Paundra et al., 2017; Steg, 2005), regarding them as “a place for me-time” and to “zone
out” (Kent, 2015). Laakso (2017) gave free bus passes to people who had relinquished their cars in a
small city in Finland: the study’s participants reported that they needed to plan more in advance than
previously or restructure routines (e.g. grocery shopping, dropping off children). But more than functional
considerations, emotions and feelings played a crucial role in building a new routine. Freudendal-
Pedersen (2009) states that cars are widely perceived as the only transport mode that gives people the
varying needs independent from time and space constraints.
Concurrently, more and more people acknowledge that cars negatively impact sustainability (Banister,
2008). Arbib and Seba (2017) predict the end of individual car ownership. However, Banister (2008)
and choice. Additionally, Spickermann et al. (2014) stress that while the emotional attachment to cars is
innovative services.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 15
A trend running in parallel is the growing demand for non-ownership services (Moeller & Wittkowski,
“possession importance” factor.
3.1.3 Windows of opportunity
Relatively recently the focus in research on travel behaviour change has shifted towards key or life events
that trigger changes in travel behaviour (Lanzendorf, 2003). Such events are “windows of opportunity”
nature of their own behaviour (Spaargaren, 1997). Studies have shown that individuals are indeed more
susceptible to interventions when a major change to the infrastructure of their neighbourhoods had
occurred, when they had recently relocated residence or workplace (Thøgersen, 2012; Verplanken & Roy,
2016), upon the birth of a child (Berveling et al., 2017) or upon selling one’s car (Laakso, 2017). Note that
studies on windows of opportunity all focus on the impact that a certain key event had on car ownership
or car use, and the subsequent consequences for active modes and public transport use. According to
Redman et al. (2013), tactics to entice car users to PT, coupled with interruptions in habitual behaviour,
can successfully instigate mode change, as long as PT services have attributes that are perceived to be at
least equally as appealing as travel by car.
3.1.4 What does this mean for Mobility-as-a-Service?
(Karlsson et al., 2017), in line with attention to lifestyles and mobility without owning a car. Moreover,
many see in MaaS a tool for instigating more sustainable travel behaviour patterns among the
population, and in particular for breaking private car dependence (Jittrapirom et al., 2017). Nevertheless,
travel behaviour inertia. The latter is relatively common among travellers, especially for work-related
people are more likely to challenge their travel habits, although not all windows of opportunities may
provide equal opportunities for adopting MaaS. Consequently, despite travel behaviour inertia, MaaS
implemented with the goal of reducing dependence on private cars might have potential.
3.2 Mobility integration, travel behaviour and preferences
travel preferences. The last section highlights implications for MaaS.
3.2.1 Denition of mobility integration, as traditionally understood
Mobility or transport8integrationisnotnew.Despitethelackofacleardenitionofthisnotion(Preston,
2010), it has been a focal point and guiding principle for the development of several transport policies
in numerous countries (Potter & Skinner, 2000), focusing on public transport integration and PT/private
8 Moststudiesdeningintegrationintransportresearchrefertotransport integration, yet studies on MaaS use mobility
“Mobility-as-a-Service”, and the fact that mobility is nowadays used with the broad meaning of “the ability to move freely
or be easily moved” (Cambridge Dictionary, n.d.). Meanwhile, “transport” has become more of a word of reference in
“a system of vehicles, such as buses, trains, aircraft, etc. for getting from one place to another”. According to Sochor et al.
(2017), offering mobility rather than transport is central in MaaS. Therefore, we will continue using the term mobility
integration in this study, but use transport integration when referring to studies using this term.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 16
ticket integration, network integration and wider integration. In an attempt to describe the concept in
ladder; this latter description was then re-used and adapted by Preston (2010). We re-adapted this
necessary to have fully completed one rung in order to access the following one. Note that sustainability
is often agreed to be the highest rung of the integration ladder (George, 2001; Potter & Skinner, 2000;
improved accessibility, environmental protection, and increased safety (Preston, 2010). According
to Potter and Skinner (2000), ‘lower’ understandings of integration are unable to deliver complete
solutions to challenges of a high order of magnitude; only a comprehensive approach stands a chance of
successfully tackling such challenges.
 Figure4 The integration ladder and its rungs; corresponding mobility integration levels (adapted from Preston (2010), Hull
(9) Integrate with Environmental, Social and
Economic Policies, e.g. 2011 Dutch National Policy
Strategy for Infrastructure and Spatial Planning
(8) Integrate with Education, Health and Social
Services , e.g. target group transport in the
(7) Integrate Transport and Land-Use , e.g. zoning
regulations, pedestrian-friendly development
paerns (Portland, U .S.)
(6) Integrate Transport Authorities, i.e. one
authority for all transport modes, for one region
(Transport for London , STIF in Paris)
(5) Integrate Passenger and Freight Transport , e.g.
cargo and passenger airports (London Heathrow,
Amsterdam Schiphol )
(4) Integrate Public and Private Transport , e.g.
Park and Ride, Bike and Ride, bus-only lanes
(2) Integrate Public Transport Fares, Ticketing
and Payment, e.g. respectively regional fare
system, PT modes with the same pass , one single
bill (Oyster pass, OV -chipkaart )
(3 ) Integrate Public Transport Services, e.g.
arrival/departure coordination, all modes at the
same place (Amsterdam Centraal, New York
Pennsylvania Station)
(1 ) Integrate Public Transport Information, e.g. app /
website with all PT schedules, possibility to plan
multimodal trips (NS Xtra Reisplanner, Google Maps )
Level 1 : Information
Level 2: Fare,
Ticketing and
Payment Integration
Level 3: Network
Level 4: Wide
Integrated and Sustainable Transport
Disintegrated and Unsustainable Transport
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 17
3.2.2 Mobility integration, travel behaviour and preferences
Research suggests that a higher level of integration in transport is more appealing to travellers than
mobility integration on travel preferences and travel behaviour.
Level 1. At present, PT information is frequently sought for routine trips and non-routine trips, and there
is growing demand for information beyond just arrival and departure times, such as crowding levels and
disruptions (Chorus et al., 2006; Matsumoto & Hidaka, 2015). By displaying multiple options in real-time,
such information systems (or ATISs, Advanced Traveller Information Systems) have the potential to make
users rethink their travel habits (Chorus et al., 2006; Kenyon & Lyons, 2003; Tang & Thakuriah, 2011)
and to allow for reductions in actual and perceived waiting times (Watkins et al., 2011). Recent studies
using rigorous statistical analyses show that improved information can lead to increases in patronage
(Brakewood et al., 2015; Tang & Thakuriah, 2012). However, Pronello et al. (2017), and Skoglund and
changes in travel behaviour away from the use of private cars, even when the trip planner can display
time savings with PT compared to private cars (Skoglund & Karlsson, 2012). ATISs may add enough
(see section 3.1.1 on travel behaviour inertia and section 3.3 on apps and travel behaviour). Note that
literature reviews reveal a generally low willingness to pay for information provided via information
systems, especially for PT information (Chorus et al., 2006; Pronello et al., 2017). There are currently
plenty of systems providing information for free, but people may be willing to pay if the system is
Today however most travellers view information integration as a basic prerequisite and care more about
higher integration levels (Chowdhury et al., 2018).
Level 2.FareintegrationisusuallyachievedviaafareschemevalidinallPTmodes,suchasa(zonal)at
fare or distance-based fare. Ticket and payment integration can be achieved via a single ticket valid for
a journey across multiple modes, and is nowadays frequently achieved via smart card technology. Fare,
cities, leading to more convenience, more freedom of choice in transport mode, occasional reductions
2003). A recent study also supports the premise that ticketing integration via smart cards can successfully
Level 3. Network integration has also delivered positive outcomes in terms of patronage, especially when
and partners, 2003). In Vienna, ticketing integration triggered a restructuring of the network, which in
turn led to increased patronage and substantial improvements for passengers in terms of travel times.
There, only a limited number of passengers saw their amount of transfers increase due to network
integration. Indeed, a major drawback of network integration is transferring, and hence potential
that the reason why PT patronage, cycling and walking is higher in Germany than in the USA is partly due
to the better integration of PT services in Germany.
Level 4. In terms of wider integration, the integration of land-use, transport and environmental policy has
garnered attention in recent decades (Candel, 2017; Geerlings & Stead, 2003; Newman & Kenworthy,
1996). A few studies mentioning impacts on travellers can be mentioned here. A study in Japan
demonstrated that integrated land-use and transport strategies led to CO2reductionanduserbenets
(in terms of generalised travel costs) (Doi & Kii, 2012). Transit-oriented development has been shown to
promote public transport use (H. Lund, 2006), as well as cycling and walking, thereby promoting physical
activity (Langlois et al., 2016). Although policies integrating transport and land-use/environmental/
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 18
of Figure 4),implementationremainsdifcult,andimpactassessmentsofsuchintegrationontravellers
remain limited (Candel, 2017; Preston, 2010).
3.2.3 What does this mean for MaaS?
Attractiveness for potential users. Research on mobility integration has primarily focused on PT integration
and PT/private modes integration. Studies show that a higher level of integration is more appealing to
level of convenience, more freedom of mode choice, and potentially cheaper and shorter journeys. Since
(see section 2.2), we can assume that MaaS initiatives with high integration levels are likely to be more
attractive to users than initiatives with lower integration levels, as Kamargianni et al. (2016) already
highlighted. Nevertheless, we note that mobility integration evolved over the span of multiple decades,
hinting at long development and implementation times, probably owing to the diversity of actors
involved. Technology may shorten these time periods, but high integration levels as standards within
MaaS might not occur in the short term.
Mobility integration and shared mobility modes.Expertsdeemthecombiningofvariousmodesoftransportas
MaaS’s most relevant impact on individuals (Karlsson et al., 2017). These various modes include shared
mobility modes. Initial signs of integration between shared mobility modes and PT have emerged.
rented at stations with a PT pass (Martens, 2007), without requiring a separate subscription. Moreover,
PT-bikes have also recently incorporated information integration via the national train company’s trip
planning app, which shows the number of available PT-bikes at any given station. Ticketing integration is
by the cooperation between STIB (PT and bike sharing operator in Brussels, Belgium) and Cambio (a
car sharing company) (Loose, 2010), and between SBB (Swiss train operator) and Mobility Car sharing.
ladder. Rung 3 for instance would become “Integrate PT and shared mobility modes services”. Arguably, the
more modes, the more challenging it is to implement “seamless transfers”. To date however research on
mobility integration and shared mobility modes remains scarce.
3.3 Changing travel behaviour through mobile applications
we shed light on key features in mobile apps aiming to promote more sustainable travel patterns, as
3.3.1 Mobile applications and sustainable travel behaviour?
mobile devices and apps in particular will be of central importance, thanks to their widespread adoption
and pervasive use (Lathia et al. 2013). Mobile applications that impact travel behaviour include apps
providing information about travel (including convenience information, such as parking, congestion,
crowdedness in PT, etc.), planning, routing, access to shared mobility modes, booking, payment, price
comparison of travel alternatives, safety and health advice, and social media apps (Gössling, 2017).
Gössling (2017) indicates that apps can use persuasion to support mode change towards “sustainable
transport choices”. Technologies to promote sustainable mobility were coined Behaviour Change
form, alter, or reinforce attitudes, behaviours or an act of complying without using deception, coercion
application. However, as indicated in section 3.2.2, the contribution of such apps to a modal shift
away from private cars remains unclear. Further, shared mobility modes (that often require the use
of an app) may generally lead to reductions in private car use, but may not necessarily lead to more
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 19
sustainable travel patterns (see section 3.4). Notably, there is an entire category of applications that
makes using private cars more attractive and hence may not serve sustainability goals (Gössling, 2017).
When zooming in on the effectiveness of BCSSs for changing travel behaviour in particular, virtually no
2017). Consequently, as suggested by Andersson et al. (2018) and Sunio and Schmöcker (2017), mobile
applications that aim to instigate more sustainable travel patterns must be more grounded in travel
behaviour change theory if they are to effectively promote change.
3.3.2 Key features in mobile apps to support travel behaviour change
To investigate the key features that smartphone application technologies need to promote sustainable
First, Andersson et al. (2018) found that customisation to the user is crucial to promote mode change, as
the literature review of Chorus et al. (2006) already underlined. According to the diffusion of innovations
theory, a product must be adapted to the user, and not vice versa (Rogers, 2003). Stopka (2014)
(2018) found that information and feedback are important for encouraging individuals to perform the
desired behaviour. Third, they found that engaging users is a key issue in terms of changing behaviour
via apps, which reminds us of travel behaviour inertia. In that sense, continuous improvement9 and
interest of users. One of the qualities that allows an innovation to spread is how simple it is to use,
without the need to learn (Rogers, 2003). That which is simpler to understand is adopted more rapidly
than that which requires new skills and comprehension.
3.3.3 What does this mean for MaaS?
Mobility-as-a-Service is to be primarily accessed on the passenger side via an application on a
smartphone or tablet. The rise of MaaS concurs with the recent growing interest in the way apps could
trigger changes in travel behaviour. Research suggests that four aspects of apps are crucial to promoting
sustainable mobility: customisation to the user, information and feedback, engaging the user, and an
of behaviour change support systems, taking into account these four features – and generally travel
behaviourtheory,asbrieyintroducedinsection3.1 – in designs of MaaS applications could help attract
users, lock them in and promote alternative travel behaviour patterns.
3.4 Shared mobility modes, travel behaviour and preferences
and sociodemographic characteristics of users and also the trip characteristics, and then we present the
highlights implications for MaaS.
3.4.1 Car sharing
Car sharing users and trips. Research shows that the people more likely to participate in car sharing are
young and highly educated adults with moderate to high incomes who live in urban areas and in
households with limited car ownership (Becker et al., 2017; Clewlow, 2016b; Kang et al., 2016; KiM,
who have a low sense of ownership and a utilitarian view of mobility. Visiting friends or family, shopping
(including shopping for heavy items), recreation and business trips are most frequently mentioned as trip
9 A key aspect to spreading an innovation, according to the diffusion of innovations theory (Rogers, 2003).
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 20
purposes; most users appear to rent cars for incidental mobility needs (Baptista et al., 2014; KiM, 2015;
Le Vine & Polak, 2017).
Price structures. Research reveals that many car owners do not have the full costs overview in mind when
purchasing vehicles (Turrentine & Kurani, 2007). Moreover, many drivers only consider the out-of-pocket
long-term costs of owning vehicles than to the running costs of a car sharing subscription.
Car sharing and PT use/walking/biking. Car sharing schemes can enable shifts towards other modes. While
station-based car sharing triggers a shift away from private vehicles and toward public transportation
integration effect), but that in many cases it reduces PT use and walking/cycling (substitution effect) in
per city), but walked more frequently.
Car sharing, private car use and car ownership. Several studies have indicated that car sharing reduces vehicle
ownership rates per capita among car sharing members, as summarised in Baptista et al. (2014) and
Shaheen et al. (2012). Martin and Shaheen (2011) note that the decrease in privately owned vehicles
is also accompanied by an average decline in VKT/VMT (Vehicle Kilometres Travelled/Vehicle Miles
Travelled) of between 27 and 43% per year. Reducing private car use is less likely to occur among
suburban car sharing members than urban ones (Clewlow, 2016a) and among individuals with high
education levels and/or high incomes (Le Vine & Polak, 2017). Martin et al. (2010) found that between 9
and 13 privately owned vehicles were taken off the road per (station-based) car-sharing vehicle, which
includes both the suppression and shedding effects. Car sharing’s suppression effect is the effect that
car sharing has on suppressing the members’ need to personal vehicles, while the shedding effect is the
than the shedding effect (7-10% and 2-5%, respectively). Similarly, Le Vine and Polak (2017) found the
the shedding effect, although shedding is more likely than suppressing among low-income households.
had reconsidered owning cars.
3.4.2 Bike sharing
All insights provided in this section derive from studies on station-based bike sharing. To the best of our
2018, and the same applies for bike sharing’s impact on car ownership.
Bike sharing users and trips. Bike sharing users are younger, have higher incomes, higher education levels
and are more likely to work full- or part-time than the average population (Fishman, 2016; Ricci, 2015).
Bike sharing users do not necessarily have lower car ownership rates than non-users (Fishman et al.,
2013). The main reasons for using bike sharing are convenience (close to work, to home, fast, short
routes, getting around more easily), followed by saving money (Fishman, 2016). Users usually praise
the time saved compared to other modes that are subject to congestion or delay (Sener et al., 2009).
Shared bicycles are typically used for short-duration trips, while trip purpose depends on the type of user,
notably long-term users (more work-related purposes) or casual users (more leisure-related purposes)
(Fishman, 2016).
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 21
Bike sharing and PT use/walking/biking. Research reveals that most people who switch to shared bikes come
provide users with considerable incentive to use bike sharing, potentially resulting in car use reduction
sharing trips replaced PT trips (DeMaio, 2009). According to Martin and Shaheen (2014), in cities with
high population densities and high public transport network densities, bike sharing decreases PT use
increases PT use in suburban areas/city peripheries.
Bike sharing and private car use. Research universally shows that bike sharing systems reduce car travel
(Fishman et al., 2014; Martin & Shaheen, 2014; Shaheen et al., 2013). Nevertheless, shifting away
substitution rate of 2% among users in London (U.K.), which contrasts with rates of 19%, 19% and
21% among users in Minneapolis/St. Paul (U.S.), and Melbourne and Brisbane (Australia), respectively.
cities with low substitution rates. The impact of bike sharing systems on road congestion is unclear
3.4.3 Ride-sourcing
Most of the available studies on ride-sourcing derive from California (U.S.); several studies have analysed
data collected there in 2015 among adults aged 18 to 50 (Alemi et al., 2017; Alemi, Circella, Mokhtarian,
et al., 2018; Alemi, Circella, & Sperling, 2018; Circella et al., 2018).
Ride-sourcing users and trips.Therateofadoptingride-sourcingissignicantlyhigheramongpeoplewho
are young adults, highly educated, work full time, have higher incomes (Alemi et al., 2017; Clewlow &
Mishra, 2017b), reside in urban areas, are childless (Alemi et al., 2017), have low rates of car ownership,
and already undertake multimodal trips (Alemi, Circella, & Sperling, 2018). Moreover, Alemi et al. (2017)
found positive correlations between ride-sourcing adoption and the frequent use of smartphones for
daily travel and social media, shopping online, and previous bike sharing and/or car sharing use. Although
ride-sourcing is primarily used incidentally (Alemi, Circella, Mokhtarian, et al., 2018), ride-sourcing trips
can account for 15% of all trips within San Francisco on an average weekday (SFCTA, 2017). Among
ride-sourcing users, the most-cited reasons for using such services are convenience, reliability, short
travel times, avoiding drunk driving, and not having to park (Alemi, Circella, & Sperling, 2018; Clewlow &
Mishra, 2017b; Rayle et al., 2016).
Ride sourcing and PT use/walking/biking.BothmodalintegrationandmodalsubstitutionwithPTexist.
depends on the demographics of the user and the availability and type of PT. APTA (2016) and Alemi,
Circella, and Sperling (2018) suggest that a complementary effect is at work, since a majority of ride-
sourcing trips are made between 22:00 and 4:00, when public transport services are limited, and owning
to “to not drink and drive” being frequently cited as a main reason for using ride-sourcing. A study
while reducing total VKT (Stiglic et al., 2018). Ride-sourcing has however been shown to compete with
Sperling, 2018; Rayle et al., 2016; Schaller, 2017). Regarding walking and biking, more than 40% of the
frequent ride-sourcing users in a Californian survey reported a decrease, and less than 10% an increase in
these active modes (Circella et al., 2018).
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 22
Ride-sourcing, private car use and car ownership.Studiesconsistentlyndacorrelationbetweenride-sourcing
adoption and reductions in private car driving: 26% of users in seven major U.S. cities reported that
they drove less after adopting on-demand ride services (Clewlow & Mishra, 2017b), with this share
increasing to 40% for San Francisco only (Rayle et al., 2016), and 70% for frequent10 users in California
(Alemi, Circella, & Sperling, 2018). More than 90% of Rayle et al. (2016) survey respondents stated that
they did not change the number of vehicles they owned after joining a ride-sourcing scheme (some
study. The more frequently a person used ride-sourcing, the more likely they were to have shed a vehicle
(Clewlow & Mishra, 2017a). Impacts on congestion remain unclear (Jin et al., 2018). Note that ride-
sourcing could induce trips: in the Rayle et al. (2016) study, 8% of respondents would not have made
Ride-sourcing and other shared mobility modes. Alemi et al. (2017) found a positive correlation between
ride-sourcing adoption and previous use of bike sharing and/or car sharing. However, frequent car
sharing use negatively correlates with ride-sourcing, indicating potential competition (Alemi, Circella,
Mokhtarian, et al., 2018). Research reveals the impact of combining ride-sourcing and car sharing: 57%
of the individuals who adopted both services are carless and reside in highly urbanised neighbourhoods,
compared to 37% for non-adopters, while 33% are carless and reside in PT-accessible neighbourhoods,
compared to 19% for non-adopters (Clewlow, 2016b). The American Public Transportation Association’s
term “supersharers” denotes people who used some combination of bike sharing, car sharing and ride-
sourcing for commuting, errands and recreational trips within the past three months (APTA, 2016).
Nevertheless, Clewlow and Mishra (2017b) found that such users still have on average higher rates of car
ownership than PT-only users. Supersharers remain a small group though.
3.4.4 Demand-responsive transport
DRT users. Initially, the growth of DRT around the world was fostered by policies aiming to ensure the
provision of transport services for people with impairments, resulting in DRT and disabilities often
technological improvements, DRT is increasingly used for new applications. Cervero (1997) highlighted
the potential of DRT in settings combining spatial dispersion and low dependency on city centres.
DRT services are increasingly used in rural areas, where they have proved to be most effective in
both meeting demand (Laws, 2009) and justifying public investments (Davison et al., 2012). Mulley
and Nelson (2009) posited that areas in urban and peri-urban settingsmightalsobenetfromDRT
type of DRT as coverage-oriented DRT services. According to the literature review of Jain et al. (2017),
eight characteristics are likely to impact the use of a DRT service: being aged 15-24, or 55 and above;
being female; not being in the workforce; not possessing a driving licence; low household income
and vehicle ownership rates; being a single-person household; and not having a train station in one’s
neighbourhood. Further, there is a higher share of people with mobility impairments among coverage-
oriented DRT users than among the general population (TCRP, 2004; Wang et al., 2014). Jain et al. (2017)
found that such services are frequently used for shopping and social purposes. DRT’s high adaptability
(Laws, 2009) also renders it relevant in high-density areas (Davison et al., 2012). We refer to this type of
DRT as urban DRT services11.AccordingtoSantietal.(2014),morethan95%oftaxitripsinNewYorkCity
around the world show similar potential (Tachet et al., 2017). A stated preference study conducted in
likely to adopt urban DRT, as are the high-income respondents (Frei et al., 2017). Another stated
preference study conducted in Amsterdam (pertaining to leisure trips) revealed that among car owners, it
10 Alemi,Circella,andSperling(2018)dene“frequent”asatleastonceamonth.
11 We do not imply that DRT cannot be used for coverage purposes and in densely populated areas. We make the distinction
here for the sake of clarity.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 23
is the highly educated, working individuals aged 50 or younger who are more likely to include urban DRT
in their mobility choices (Alonso-González et al., 2017). This study also revealed that more multimodal
DRT and travel behaviour. Coverage-oriented DRT is designed, and often subsidised, to substitute and
complement public transport, where/for whom other alternatives are limited (rural areas, people with
impairments, etc.). Moreover, literature on urban DRT remains relatively limited. Studies suggest that
urban DRT use may reduce walking, biking and PT use, but the complementary/substitution effects,
notably with PT, are as yet unknown and could depend on the design of the DRT service (Alonso-
González et al., 2017; Frei et al., 2017; Gunay et al., 2016; Jokinen et al., 2017).
3.4.5 What does this mean for MaaS?
Changes in travel behaviour.Studiesshowthatsmallcarsuppressionandsheddingeffectsdoexist,which
and often depend on built environment characteristics. Table 2 provides an overview of the effects of
shared mobility modes on travel behaviour. Note however the unequal degree of knowledge about the
various modes (e.g. we know more about bike sharing than urban DRT; consequently, more uncertainties
see Fishman (2016)).
 Table2 Overview of the effects of shared mobility modes on travel behaviour.
PT use Active modes
Private car
Car ownership VKT (Vehicle
Car sharing
(+) (+) (-) (-) mostly for urban
dwellers, suppression
and shedding effects
depending on
household income
Car sharing
(+)/(-) (-)/(+) (+)
Bike sharing (+) in suburban
areas of densely
populated cities / (-)
in city centres with
high population and
PT network densities
(+) for cycling
/ (-) for
(-) (?) (+)/(-)
Ride sourcing (+)/(-) (-) (-) (-) for frequent users (?) (potentially
Ride sourcing +
car sharing
(?) (?) (-) (-) stronger effect
than ride sourcing or
car sharing alone
oriented DRT
In these cases, DRT is designed to substitute and complement public transport. Other
alternatives may be limited for users (no PT available, mobility impairment, etc.).
Urban DRT (?) (potentially (-)) (-) (based on
1 study)
(-) potentially (?) (?)
(+): Increase in general
(-): Decrease in general
(?): Impact still unclear or unknown
(+)/(-): Sometimes increase, sometimes decrease.
For nuances, the reader can refer to the above sections and cited references.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 24
Users’ proles and the question of access to transport. By design, shared mobility modes are usually situated
in areas with high population densities, where they are more commercially viable (Agatz et al., 2012).
A (potentially unintended) pre-selection of users already occurs, owing to the fact that these shared
of typical users are relatively comparable across these modes (car and bike sharing, ride-sourcing,
urban DRT): often younger people with higher incomes and education levels who are more likely to
be employed than the average population. A strong focus on these modes in MaaS and a potential
especially when public subsidies are involved (with shared mobility modes or PT). Further, as noted by
Jin et al. (2018) regarding ride-sourcing, the question of the ‘digital divide’ remains relevant for a service
like MaaS. This term originally referred to unequal access to ICT and the skills required to use it (Selwyn,
(Jin et al., 2018). Shared mobility modes can require such technology and MaaS would also likely require
it. However, smartphone (and mobile data) use is arguably not easy for everyone, even in countries
with high smartphone penetration rates, and hence a sharp digital divide remains (Poushter, 2017).
New technologies pertaining to mobility have the potential to give people more possibilities, yet also
(2018) for car sharing, Fishman (2016) for bike sharing); it is unlikely that these barriers would simply
disappear when such modes are integrated in MaaS, and therefore they will also need to be addressed.
Price structure. Note that the price structure of MaaS is comparable to the price structure of car sharing
as car sharing’s price structure does, even when maintaining the status quo is not the cheapest option.
Types of trips. The types of trip purposes with shared mobility modes usually depend on how frequently
such modes are used, with infrequent users tending to make more casual (e.g. leisure) rather than
time-critical trips. Nevertheless, a majority of shared mobility modes members use these services on
an incidental basis, which suggests that: (1) MaaS including shared mobility modes may initially only be
used for casual and incidental trips, and that (2) a heavy focus on commuting trips in the initial stages
Reliability with shared mobility modes. As emphasised by Van Hagen and Bron (2013), reliability – and
safety – is an essential prerequisite for passengers. Shared mobility modes introduce new meanings of
reliability, which differ from the usual meaning of reliability in conventional public transport, because
product-related resource will be unavailable when a consumer desires access”, and they demonstrated
that a perceived risk of product scarcity due to competition for the shared product could be a key
inhibitor to participating in a commercial sharing program. Fricker and Gast (2016) demonstrated that
even a low probability of unavailability of shared bikes may deter use, especially for individuals that rely
on them daily. Additionally, Weckström et al. (2017) found that long response times and unavailability of
vehicles were the main reasons why higher income groups discontinued their use of Kutsuplus, an urban
DRT service. In addition to the unguaranteed availability upon departure, other aspects could affect the
shared vehicle on time (ter Berg & Schothorst, 2015) and transfers within schedule-free modes, or from
a schedule-free mode to a schedule-bound mode (and vice versa). Such uncertainties about reliability
could have consequences for MaaS’s adoption and use.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 25
3.5 Conclusion
Based on the nine core characteristics of MaaS as described by Jittrapirom et al. (2017), we have selected
and discussed three relevant themes. Where these three themes intersect – as depicted in Figure 5,
an annotated version of Figure 3 –, coupled with an understanding of the MaaS concept and travel
behaviour theory, provides some insights and discussion points about Mobility-as-a-Service and its
potential for instigating changes in travel preferences and travel behaviour, as summarised below.
 Figure5 Thethreethemesandtheirintersectionsasdiscussedandaddressedinthisexplorativeliteraturereview.
close to
 Newformofexibility
relatively unlikely in the short term and unclear over the longer term. However, MaaS seemingly has
It may also hold promise to instigate changes in travel behaviour and preferences among them,
potentially in a more sustainable direction. Nonetheless, it is crucial to take various aspects into account
when pursuing a widespread adoption of MaaS and change in travel patterns. First, research on mobility
integration reveals how challenging the integration process is. A higher level of integration is more
attractive to travellers; however, developing and successfully implementing such integration is a long-
of mobile applications that aim to support changes in travel behaviour (so-called Behavioural Change
Support Systems). Research reveals that four app features in particular are necessary conditions, yet they
majority of cases, using such modes remains incidental and must not be automatically associated with
more sustainable travel patterns. Integrating these modes within MaaS has the potential to provide an
generally, problems associated with social inclusion.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 26
4 Systematic literature
review of the potential
impact of MaaS on travel
preferences and
In this section we present a literature review of the potential impact of MaaS on travellers’ preferences
preferences. This section is therefore structured as follows:
Introduction: Presentation of the selected papers and the associated research methods.
Theme 1: A change in the private car ownership paradigm?
Theme 2:PreconditionsinMaaS:theneedforautonomy,exibilityandreliability
Theme 3: Aspects adding value in MaaS
Theme 4: The user-side design of MaaS
Theme 5: Costs and willingness to pay
Theme 6: Travellers’ characteristics
4.1 Presentation of the selected papers and the associated
approach? Here we provide some insights into the representativeness of the studies’ samples, as
well as information about research methods that can be important to bear in mind when reading and
interpreting the results (e.g. limitations of certain research methods).
4.1.1 Selection of relevant papers
nalselection,weretain14papersthatcanbeclusteredintotwogroups,aspresentedinTable 3.
ThetypeofstudyandresearchmethodsarealsobrieypresentedinTable 3. Note that in the systematic
literature review (section 4.2 to 4.7) we use a few other references for illustration purposes or to provide
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 27
 Table3 Results from the systematic literature search conducted in May 2018 on Mobility-as-a-Service and its potential
impacts on travel preferences and behaviour.
Year Authors Typeofstudyandresearch
study is conducted
papers on
MaaS pilots/
linked to
MaaS pilots
2016 Strömberg,Rexfelt,
Karlsson and Sochor
Comparative analysis of two
cases studies (one is UbiGo) in
light of Rogers’ diffusion of
innovations theory.
Gothenburg (Sweden)
2015 Sochor, Strömberg and
(qualitative and quantitative:
surveys, interviews and travel
diaries for a few days (UbiGo)).
2016 Karlsson, Sochor and
2016 Sochor, Karlsson and
2018 Strömberg, Karlsson and
2015 Smile mobility* Vienna (Austria)
2017 Karlsson, Sochor,
In-depth evaluations of UbiGo
and Smile
Interviews and
2018 Smith, Sochor and
Development of MaaS
scenarios through interviews
with professionals.
West Sweden
2017 Ho, Hensher, Mulley and
Survey research: Stated
monthly bundles.
Sydney (Australia)
2017 Ratilainen* Helsinki (Finland)
2018 Matyas and
London (UK)
2017 Alonso-Gonzáles, Van
Oort, Cats and
Survey research: Stated
mode choice.
Amsterdam (The
2017 Haahtela and Viitamo Evaluationofthepotentialof
MaaS through a survey and
focus groups.
2018 Kamargianni, Matyas, Li
and Muscat*
the potential of MaaS through
attitudinal research.
London (UK)
4.1.2 Research methods
Overview of methods. Pilot and survey research are often used to make quantitative statements about
the impacts of MaaS on travel preferences and travel behaviour. Survey research was either used as a
complement, as in the case of evaluating UbiGo, or as a main method for gathering information about
MaaS, and was occasionally preceded by a more quantitative approach, such as Haahtela and Viitamo
(2017) using focus groups to assist in the survey’s design. When used as a main method for acquiring
information about MaaS, attitude research and stated preference (SP) research are often used. G. Smith
et al. (2018) took a different approach than the rest of the selected studies: they conducted interviews
with private stakeholders, in which PT and MaaS were discussed. They then performed a structured
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 28
Pilots.Evaluationsofpilotstypicallyusedvariousmethods,aspresentedinTable 3. Additionally, these
pilots differed in multiple aspects, as shown in Table 4. Both pilots primarily targeted young or middle-
aged urban dwellers. Moreover, the participants agreed to sign up for such trials and seemingly genuinely
enjoyed the possibility of trying a new service (Sochor et al., 2016). The participants were not particularly
deterred by prices, especially in the case of UbiGo, which worked with monthly bundles (see section
4.6 for bundles’ prices). Karlsson et al. (2017) found that UbiGo was particularly more attractive for
households of more than one person situated in the city centre of Gothenburg, where car sharing and
PT provision are good. Based on data from Sochor et al. (2015) and Karlsson et al. (2016), at least 90%
of UbiGo households seemingly earned more than the gross medium income in Gothenburg. All told,
the pilots’ results may not apply to the entire population of these respective cities and countries,
According to Strömberg et al. (2016), selective pilot recruitment increases the chances of success, and,
consequently, creates observability (a wide audience can see that it works) – showing that a sustainable
modal shift is possible.
 Table4 Overview of Smile and UbiGo pilots (Karlsson et al., 2017; Smile mobility, 2015; Strömberg et al., 2018).
Smile UbiGo
Type of MaaS pilot* Level 2 Level 3
Pilot duration 6 months (from November 2014) 6 months (from November 2013)
Amount of pilot
Over 1,000 195 people in 83 households
Amount of survey
Around 170 (end-pilot survey) 164 before-pilot, 161 during-pilot, 160
end-pilot, 109 6-month follow-up
Characteristics of the
sample of participants
Matched the gender and age distribution for
early adopters.
The average Smile user is male, aged
between 20 and 40 and has a high level of
education and high income.
Overrepresentation of city centre
inhabitants, retired people greatly
* See section 2.2.
Attitudinal research. An attitude is a group of opinions, values and dispositions to act associated with
a particular concept. Attitudes can be measured by showing respondents statements pertaining to a
deeper insights into intrinsic motivations for using or not using MaaS.
Stated preferences studies. Stated Preference (SP) techniques are frequently used to gather information
about products and services that are not yet available (Louviere et al., 2000). In discrete choice SP,
attributes (e.g. travel time and price) that usually have two to three levels (e.g. €10, €25, €40 for
Kamargianni (2018), and Ratilainen (2017), respondents chose their favourite mobility bundle from a
given selection, with the aim being to understand which types of bundles might appeal to potential users
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 29
In Alonso-González et al. (2017), respondents were asked to choose between different modes that may
portfolio”) for residents of Amsterdam.
Shortcomings of SP and attitudinal research.ThemostcommonshortcomingofSPexperimentsisthat
necessarily translate into the same choice in real life, owing to a wide variety of decision factors and
a certain bundle with modes they have not used before, will they actually use them? Matyas and
Kamargianni (2018) found that 64% of their respondents answered positively to the statement, “I would
be willing to try transport modes I previously didn’t use if my MaaS plan included them”. Although
this looks encouraging for modes like bike sharing, car sharing and DRT, it could still be that while
their travel habits and adopt modes they previously did not use. Further, the potential for hypothetical
behaviour; it is common to see people failing to practice what they preach (J. R. Smith & Louis, 2007) and
multiple studies in the past have reported low or inconsistent correspondence between attitudinal and
behavioural entities (Ajzen & Fishbein, 1977).
Representativeness of samples.Eachofthesurveystudiesincludesamplesthataremoreorless
representative for each metropolitan area, which can be useful to bear in mind when interpreting the
results. Details of the representativeness of each sample are shown in Table 5; overall, there is a good
degree of representativeness. All studies targeted people aged 18 or above.
 Table5 RepresentativenessofsamplesinsurveystudiesonMaaS(excludingevaluationsofpilots).
Study* City(and
Matyas and
Kamargianni (2018)
London 1,068 Representative of the population in terms of age and gender,
over-representation of full-time employed and retired
Kamargianni et al.
London 1,570 Representative of the population in terms of gender, age,
residential zone and driving license possession. Over-
representation of Caucasian British.
Ho et al. (2017) Sydney 252 Well representative for the worker population but under-
representative of retirees and housekeepers.
Alonso-González et al.
Amsterdam 797 Slightly under-representative of the elderly and low-
educated people (compared with the Dutch population),
representative otherwise.
Ratilainen (2017) Helsinki 252 Over-representation of females, older age categories and
people with low-income.
* Haahtela and Viitamo (2017) is not included here because the paper mainly focused on focus groups and the
complementarity between focus groups and survey.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 30
4.2 A change in the private car ownership paradigm?
4.2.1 Private car use and MaaS in practice
A recurring discussion in the selected studies is private car use reduction. Pilots reveal that MaaS can
engender a decrease in private car use. In Vienna, 21% of participants in the Smile pilot reduced the
use of their private cars (Smile mobility, 2015). In Sweden, 44% of UbiGo participants also decreased
their use of private cars during the trial (Karlsson et al., 2017). Participants became less positive towards
private car use and more positive towards use of alternative modes (Sochor et al., 2015). Strömberg et
Car shedders (13%), i.e. people who wanted to relinquish ownership of their cars because they were
reduced their private car use.
Car accessors (30%), i.e. people who wanted to gain access to a car without owning one, hesitating to
purchase one for the same reason that car shedders wanted to relinquish theirs. 37% of them reduced
their private car use.
services. Around 20% of them reduced their private car use.
using their private cars less during the trial.
Note that before the pilot, UbiGo participants were incentivised to relinquish (one of) their car(s) during
which 88% were single-vehicle households, and none changed their minds during the 6-month trial
(Karlsson et al., 2016).
4.2.2 Owning versus using
In the same line, the dichotomy of owning versus using, in the sense of privately owned car versus
sharing a vehicle and/or space in a vehicle, is also a recurrent topic in the selected studies. In London,
67% of non-car owners believe there is no need to own cars, regardless of their age or area of the city
they live in (Kamargianni et al., 2018). Moreover, 36% of the non-car-owning participants stated they
would delay purchasing a car and 40% that they would not purchase a car at all if MaaS were available.
In UbiGo, 78% of the car accessors increased their use of car sharing and 30% increased their use of car
rentals (Strömberg et al., 2018). Regarding car owners in London, one in three stated that they would
like to have access to a car without owning one, and one in three agreed that MaaS would help them
depend less on their cars, while one-fourth of car owners stated that they would even be willing to sell
their cars for unlimited access to car sharing (Kamargianni et al., 2018). The researchers nevertheless
noted that half of the car owners were attached to their cars and did not like the idea of only having
access to a car without owning one; around half of the car-owning respondents in London disagreed with
the statement, “MaaS would help me depend less on my car”. Additionally, residing in the countryside
of living and commuting (daily with a private car) aligns with one’s values (Haahtela & Viitamo, 2017).
In light of our previous discussion on car ownership in section 3.1,suchndingsarenotverysurprising:
(Freudendal-Pedersen, 2009).
Note though that the dichotomy of owning versus using presents gradations, hybrid forms where using
that the diffusion of MaaS will allow for a decrease in car ownership, and more precisely that urban and
a particularly good option as a replacement for second cars, or for households considering investing in a
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 31
second car. The combination of shared mobility modes and public transport would therefore provide an
alternative for second cars. In this perspective, what role would public transport play in MaaS?
4.2.3 The role of public transport
According to Hensher (2017), the MaaS era could disrupt the current role and organisation of public
transport. Matyas and Kamargianni (2018) and Ho et al. (2017) state that PT should be the backbone of
MaaS – at least in metropolises such as London, Sydney and Vienna. Both studies found that respondents
have a preference for mobility bundles that include public transport, especially unlimited public
transport. In Vienna, 48% of Smile users used PT more often (Karlsson et al., 2017). Note though that not
all public transport users might switch to MaaS: mobility bundles were not attractive to frequent public
transport users in Sydney for economic reasons. Moreover, the focus group and survey participants
of Haahtela and Viitamo (2017) (cities as well as small towns) mentioned several improvements that
must be made to public transport before they would consider switching (more frequently) to buses
for improvement included being able to work during commutes, with quiet spaces, power sockets and
Internet connections. Pilots in urban regions found increases in public transport use among participants:
48% of respondents to Smile’s post-pilot survey stated that they used public transport more often,
while all groups in UbiGo used public transport more often, including up to 60% more often for the
they would substitute car use for public transport if MaaS was available, although one can argue that the
If such a shift does take place, this could lead to crowding in PT vehicles and at stations (Kamargianni
et al., 2018). Alternatively, if MaaS with car sharing were available, 12% and 22% of regular public
transport users stated they would substitute part of their public transport trips with car sharing and
taxi12, respectively. Some of the transport professionals interviewed by G. Smith et al. (2018) believe that
PT users gaining easier access to car-based services could lead to the cannibalisation of public transport
also contribute to this phenomenon (G. Smith et al., 2018), thereby possibly limiting MaaS’s positive
use. In the study of Kamargianni et al. (2018), 14% of regular PT users stated that they would substitute
part of their PT use with bike sharing: some of the potential decrease in PT use with MaaS might result
from substitution with active modes, when distances allow.
4.3 Preconditions in MaaS: the need for autonomy, exibility
and reliability
4.3.1 The need for autonomy and exibility
private cars less frequently. The end-pilot evaluation revealed that they had overestimated their car
use (car rental and shared cars) by 30% on average, preparing “for a need that never materialised” (as one
in willingness to pay (WTP) in a bundle between one-way car sharing (WTP = around $7.27 Australian
dollars) versus round-trip car sharing (WTP = 0), as observed by Ho et al. (2017). Moreover, Haahtela
12 Theresearchersalsoindicatethatrespondentsareinfavourofusingtaxiasasharedoption(i.e.DRT),butnoquantitative
information is available on this topic.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 32
autonomy of a private car for trip chaining13, whether it be for work (meetings in diverse locations) or
private purposes (picking up children at school, grocery shopping after work, etc.).
pertaining to the design of MaaS. Matyas and Kamargianni (2018) found a preference for car sharing
appreciated the fact that the app took into account their privately owned transport modes in the trip
participants desired a pay-per-use system based on money rather than credits (hours of car sharing
4.3.2 New meanings of reliability
As previously discussed in section 3.4.5, reliability is a prerequisite for passengers, yet shared mobility
Ho et al. (2017) found that people prefer not having to book shared cars in advance, meaning they are
willing to pay more for last-minute availability. With every 15-minute increase in advance booking, the
researchers estimated that the willingness to pay would decrease by around $1.00 Australian dollar.
Ratilainen (2017) found that what matters more to people when using DRT is the pick-up speed promise
– being certain about the pick-up time, the assurance that one will be picked up on time – rather than
the duration between booking and availability. Further, as part of the service in MaaS, participants in the
Haahtela and Viitamo (2017) focus groups highlighted another form of reliability: namely, they want to
be provided with adequate and accurate routing when PT delays occur.
4.4 Aspects adding value in MaaS
4.4.1 Choice freedom
UbiGo participants enjoyed having access to the wide palette of transportation services offered on a
single platform (Sochor et al., 2016), and valued the high degree of choice freedom, notably the varied
bus or electric bike), but also of vehicles (e.g. shared electric city car or shared family car). According to
modes will be key for the groups in which private cars will be less important in future. Choice freedom
of new mental models (Strömberg, 2015). UbiGo participants also stressed that car sharing sites must be
potential by Karlsson et al. (2017) found that such a service would mainly attract households in areas
where PT was readily available both in terms of routes and frequency, and with car sharing vehicles
to enjoy increasing freedom of choice in how they make trips, demand for high-level autonomy and
13 By trip chaining, we refer to a sequence of trip segments beginning at the ‘home’ activity and continuing until the traveller
returns ‘home’ (Primerano et al., 2008), for instance home > work > restaurant > home.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 33
4.4.2 Convenience and value of an advanced level of integration
UbiGo users gained a new understanding of what convenience means to them thanks to the service’s
all-inclusiveness (Sochor et al., 2016), and this perception of all-inclusiveness was reinforced by the trust
the participants had that any problem would be promptly dealth with (Sochor et al., 2015). In Vienna,
55% of Smile users stated they more frequently combined different transportation modes, mainly cars
and public transport (26%) and bike and public transport (26%) (Karlsson et al., 2017; Smile mobility,
2015). This increase in mode combination can be attributed to the Smile app’s high level of integration,
whereby multiple modes could be booked together within a single trip. 48% of respondents stated that
their travel behaviour had changed since using the app, including using faster routes, combining different
modes, and subscribing to new mobility offers (Smile mobility, 2015). The focus groups of Haahtela and
mobility integration.
4.4.3 Tailored offer
Literature on smartphone apps and travel behaviour shows that to have a chance at instigating changes
in travel behaviour, it is crucial for the service to be tailored to the user (see section 3.3.2). This is
the participants stated that they had increased their use of alternative modes, especially car sharing and
Ho et al. (2017) noted that when respondents were offered the choice of creating mobility package
themselves, they often replicated their current travel patterns, something which the researchers had
already been partly capable of doing thanks to a detailed questionnaire completed prior to the SP
bicycle users plans that included bike sharing. Kamargianni et al. (2015) use the term “collaborative
customisation” to describe the process of dialogue between customers and providers, with the former
capable of articulating their needs so that the latter can use that information to create customised
services or products. While many sectors refrain from engaging in this type of customisation, as it results
in too many different products to produce, Kamargianni et al. (2015) argue that this is not an issue in
MaaS given the non-physical nature of the service. According to the researchers, three elements are
and attitudes and perceptions. However, they also note that since people are only capable of answering
limited numbers of questions before becoming irritated or confused, the information collecting process
and service must be smartly designed. Last but not least, such a tailor-made offer requires the user to
accept sharing data about their preferences. The question of data privacy is therefore crucial.
Note that the customised or tailor-made offer discussed in this section is part of, but not equal to,
the “customisation to the user” feature detailed in section 3.3.2. Indeed, the latter also refers to the
customisationoftheapplicationinterface,forexample,asdiscussedinsection4.5.2 below.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 34
4.5 The user-side design of MaaS
4.5.1 The design of mobility bundles
Why so much focus on mobility bundles in MaaS literature? Matyas and Kamargianni (2018) argue
that MaaS could be used as a tool for altering the way people perceive travel alternatives, rather than
physically altering the alternatives, and thereby potentially promoting shared mobility modes and PT,
for instance. Indeed, literature on transport passes and season tickets (i.e. PT mobility packages) shows
2001). Bundling is frequently utilised to increase consumer acceptance and contribute to the diffusion
of underutilised products or services, particularly when such products are bundled with more familiar
products (Reinders et al., 2010; Sarin et al., 2003). Matyas and Kamargianni (2018) found that even
though a bundle might include modes that individuals do not prefer, this does not mean that they would
not purchase it. In 22% of their choice tasks, the MaaS product – i.e. a bundle of modes, discounts and
respondents said they would actually consider purchasing it. The researchers noted that many individuals
who did not previously use car and bike sharing said they would now be willing to purchase bundles
containing them, and therefore perhaps be willing try these modes.
4.5.2 The design of the service
One reason why UbiGo allowed for changes in travel behaviour was the fact that the service was easy
enough to use (Karlsson et al., 2016), which accords with the importance of simplicity in ICT systems
that aim to change travel behaviour (see section 3.3.2). When Kamargianni et al. (2018) asked people
about potentially committing to a MaaS service, they discovered that the service must be carefully
designed in order to attract people and lock them in. More than a half of their respondents said they
would worry about running out of their subscribed amounts (of trips, kilometres, duration) in MaaS,
while nearly half of the respondents also stated that subscribing to MaaS would make them feel
trapped. When considering the answers per age group, Kamargianni et al. (2018) found that 52% of the
respondents aged 40 and above felt uneasy about the multiple characteristics of subscription services
and were nervous about committing to a MaaS subscription. This shows that in addition to the type of
service provided in MaaS, the design of the service’s basic elements is essential, particularly for reaching
certain age groups. Further, as previously mentioned, the design of the service can potentially enable
Another reason why UbiGo allowed for changes in travel behaviour was its trialability14 aspect
people to trial behaviour without strict commitments, and this could potentially ease people into the
travel behaviour change process, thereby creating observability for local policy and the public (Strömberg
et al., 2016).
4.6 Costs and willingness to pay
4.6.1 Willingness to pay and added value
Price is a preoccupation of travellers generally and hence a key aspect of MaaS. In UbiGo, households
chose bundles costing on average €200, with the cheapest option €135 (Karlsson et al., 2016).
14 Trialability,the“degreetowhichaninnovationcanbeexperimentedwithonalimitedbasis”,isinfactalsooneofthemain
qualities of an innovation that allows it to spread (Rogers, 2003).
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 35
al. (2017) underlines the fact that such a service only attracts those users for whom it is an economically
of these conditions must be met in order to allow for lasting changes. Sochor et al. (2016) argue that
offer, convenience) add value15comparedtopeople’sprevioustravelsolutions,whichcouldexplain
the willingness to pay (Rogers, 2003). And developing an all-inclusive service – “the service of the service
have more sustainable travel preferences and behaviour.
4.6.2 Subscription price sensitivity and incomplete comparison with car costs
(Ho et al., 2017; Matyas & Kamargianni, 2018; Ratilainen, 2017), which accords with the discussion in
section 3.4.1onxedandrunningcostsinsubscriptionsystemsversusprivatecars.Althoughthereare
would be willing to switch to shared cars if prices and service levels are right for their needs (Haahtela &
Viitamo, 2017; Kamargianni et al., 2018).
4.7 The importance of travellers’ characteristics
4.7.1 Current travel behaviour
Current travel behaviour and attitudes towards MaaS and travelling generally may be key components
for understanding if and how MaaS might change people’s travel preferences and behaviour.
This is shown by the segmentations done by Strömberg et al. (2018) (see section 4.2.1). The various
segmentations applied in other studies also show that current travel behaviour must be carefully
the differences between car owners and non-car owners, who consequently might need to be introduced
to MaaS differently. Ho et al. (2017) found that very frequent car users (four days per week or more) who
took few or no public transport trips were among the least likely to adopt a MaaS bundle, and thus to
change their travel behaviour.
4.7.2 Travelling and ICT skills, social inclusion
As previously mentioned in section 3.1.1, travellers are in general behaviourally inert. Survey studies
suggest that travellers indeed often prefer the status quo (Ho et al., 2017; Ratilainen, 2017). Moreover,
ride-sourcing and urban DRT studies reveal that the more multimodal an individual is, the more likely
they are to adopt these modes. However, travelling skills16 not only play a role in shared mobility modes
adoption, but seemingly also in MaaS adoption generally, as shown by Alonso-González et al. (2017).
respect, the trialability aspect could play a major role as noted by Strömberg et al. (2016). It is also worth
noting that Alonso-González et al. (2017) consider MaaS-prone behaviour as the behaviour of someone
engaging in mobility app usage on a weekly basis. On the user side, MaaS is to be primarily accessed via
apps, hence the crucial role of ICT skills. In that sense, age is likely to play a role in the adoption of MaaS.
Studies show that young adults17 are generally more likely to adopt MaaS than the older generations
15 Theaddedvalueortherelativebenetisanimportantattributefortherapiddiffusionofaninnovation,accordingto
Rogers (2003).
16 Denedhereasbeingfamiliarwithusingmultiplemodes,andinparticularnon-privatelyownedmodessuchaspublic
17 The upper age limit of “young adult” varies per study, from 34 to 39 years old.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 36
(Alonso-González et al., 2017; Kamargianni et al., 2018), which brings us back to discussions about the
digital divide, access to MaaS generally, and inclusion, as noted in section 3.4.5. Karlsson et al. (2017)
due to potential commercial interests.
4.7.3 Sociodemographic and socioeconomic status, cultural aspects
Other characteristics are likely to play roles in the adoption of MaaS. Alonso-González et al. (2017) show
that highly educated people are more likely to adopt MaaS. Ho et al. (2017) found via their survey that
age and number of children in the household may impact MaaS subscription, which was also a main
were less interested in MaaS, as was also suggested in interviews with UbiGo users (Karlsson et al.,
opinion collection technique (Jittrapirom et al., 2018).
In addition, Haahtela and Viitamo (2017) found that cultural aspects will also likely play a role in adopting
services, ordering groceries at home, using the Internet to search for travel information, book and pay
for trips. Moreover, they noted that Finland has a less developed service-oriented culture than Austria or
the Finnish commuters they surveyed were perhaps not yet fully ready to engage in MaaS.
4.8 Conclusion
MaaS pilot studies provide useful insights into travel behaviour, as they work with actual changes
in behaviour rather than hypothetical ones. Yet in order to be able to draw conclusions on travel
preferences and travel behaviour with MaaS for a larger share of the population, it is necessary to
review provides a balanced overview of the current state of research on MaaS and travel behaviour.
Studies show that generally MaaS could provide enough added value to allow certain groups of travellers
to consider adopting this service. Young to middle-aged people residing in urban areas are likely to be the
1 Thereremainshighdemandforautonomy,exibilityandreliability,prerequisitesforadoptingMaaS.
2 Itmustbeeconomicallyfeasibleforpeople/households,andpricesmustbejustiedbysufcient
could be provided via attractive service designs and high levels of integration. Moreover, pilots have
demonstrated that high levels of integration may allow for shifts from private car use to alternative
3 Currentliteratureonlyprovidesverylimitedquantiedindicationsaboutwhotheseearlyadopters
Moreover, age and place of residence, and other socioeconomic, sociodemographic, cultural characte-
ristics and skills, are likely to play roles in adopting MaaS and subsequently potentially changing travel
such changes. The positive contribution of MaaS towards achieving sustainability goals is consequently
still unclear. Table 6 summarises the aspects that are likely to play roles in adopting MaaS and changing
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 37
travel behaviour among travellers, and shows the types of studies that highlight the importance of
each aspect.
 Table6 List of aspects playing a role in the adoption of MaaS and potential changes in travel behaviour, according to the
Typeofaspect Aspect PR1SIR2
Trip-specicaspect Convenience of the trip with MaaS x x
Choice freedom within MaaS x x
Flexibility x x
Autonomy x
Reliability of shared mobility modes x
Service-specicaspect Ease-of-use x x
Customisability of the service (tailored to one’s needs) x x
Trialability x
High level of integration, including product bundling x x
Costs aspect Costs, willingness to pay x x
Travellers’ characteristics Sociodemographic, socioeconomic and cultural characteristics x x
Past and current travel behaviour, travelling skills x x
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 38
5 Conclusion and agenda
for further research
5.1 Conclusion
In times when many see in MaaS a tool for instigating more sustainable travel behaviour patterns
about MaaS’s potential impacts on travel preferences and travel behaviour. Two pathways are used to
behaviour conducted outside of MaaS, and a systematic literature review focused exclusively on MaaS, travel
preferences and travel behaviour.
Generally, the reviewed studies show that MaaS has the potential to reach certain travellers, to support
decreases in private car use and to instigate different travel patterns among these travellers. However,
the impact magnitude and direction of these changes remain relatively uncertain and require more
quantitative results, whether on the individual level (travel behaviour, travel preferences) or societal level
be impacted also remains unclear, as is the timeline for wider adoption among the population. Indeed, it
is unlikely that a drastic shift from the private car ownership paradigm to the MaaS paradigm will occur
within a few years.
Current literature can however inform us about the preconditions for adopting MaaS and for subsequent
changes in travel behaviour patterns, while also providing qualitative indications of potential users
and impacts.
5.1.1 Preconditions for adoption of MaaS and subsequent changes in travel behaviour
Studies consistently agree that it is particularly challenging to change travel behaviour when no trigger
potential for incidental trips. However, to allow such for trips to occur, individuals must actually start
adoption of MaaS, conditioning a subsequent potential change in travel behaviour, is likely to require
a combination of multiple aspects. First, it is important that MaaS adds enough value for travellers.
MaaS pilots show that choice freedom, tailor-made offers and increases in travel convenience – notably
through high levels of integration – can positively impact MaaS adoption. The need for such “tailor-
made all-inclusiveness” is especially valid if the asking price is higher than what travellers are used
to. This leads to the second point about costs: to provide travellers with a viable, lasting alternative,
adopting the service must be economically feasible. In that sense, customising the type of offer to the
user will likely play a key role. Adopting the service must also be perceived as economically feasible;
the latter might need to be introduced to MaaS in a different manner than non-car-owners. Third, it is
and reliability demands. Being able to combine modes during a trip is deemed a key strength of MaaS.
suchasMaaS,yettheirniteandexiblenatureraisesquestionsaboutreliability.Fourth,a particularly
important point is a smart design of the MaaS user interface, rendering it accessible for everyone.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 39
5.1.2 Preconditions for MaaS’s potential to challenge travel behaviour patterns
A smart design of the user interface is one feature of behavioural change support systems. In order
to have a chance to instigate new travel behaviour patterns, it is likely that the MaaS user interface
(e.g. a smartphone application) needs to include all of these features, i.e. customisation to the user,
information and feedback, commitment, and an appealing and simple design. However, these features
such aspects arise from a high degree of mobility integration. MaaS’s levels of integration are currently
(4) integration of societal goals. Research reveals that a comprehensive approach combining multiple
levels of integration is more likely to encourage passengers to use the integrated modes than solely
patterns. Generally, MaaS studies regard mobility packages as having the potential to alter the way
people perceive travel alternatives rather than physically altering alternatives, thereby potentially
promoting the use more sustainable modes, and notably shared mobility modes. The latter have proven
5.1.3 Potential MaaS users
to MaaS from a more traditional mobility paradigm. Current literature only provides very limited
quantiedindicationsaboutwhothesetravellersare,andnoquanticationaboutthe extenttowhich
changes in travel behaviour among the wider population remains uncertain. Skills, values (like a low
sense of ownership), age and place of residence, and other socioeconomic, sociodemographic and
cultural characteristics are likely to play roles in the adoption of MaaS and potential subsequent changes
in travel behaviour.
5.1.4 Impacts of MaaS
This study named a few impacts that MaaS could have. In particular, we note that the question of
who MaaS will reach raises questions that only a few studies have addressed: namely, MaaS’s impact
on (perceived) access to transport and social inclusion. Shared mobility modes could provide a good
could impact a wide range of dimensions through the changes in travel behaviour it could trigger,
including environmental sustainability (e.g. air pollution, noise pollution) and the transport system
generally (e.g. capacity optimisation, passenger demand). However, at such a preliminary stage in this
of this uncertainty is MaaS’s impact on sustainability via car use: while MaaS’s access-based paradigm
may compel decreases in private car use, it may also provide access to motorised vehicles to people
who previously did not have such access. In order to make conclusive statements about such effects,
more research about MaaS adoption and travel behaviour within MaaS is required, especially on the
quantitative side.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 40
5.2 MaaS research agenda
few MaaS-related studies available, the subject is topical, as shown by the fact that the vast majority of
relevant studies were published in 2016, 2017 or 2018.
MaaS adoption and travel behaviour change. A wide range of impacts must be researched generally, including
of MaaS’s impact on health, sustainability, the transport system, land use, etc. Many people quickly
adoption of MaaS and decisions within MaaS, especially on the quantitative side. Only then can the
impacts be derived in terms of measurable goals (e.g. Vehicle Kilometres Travelled). Quantitative
but research on MaaS is also relevant for non-urban areas. Ultimately, it is crucial for MaaS research to
also focus on groups of people who are not necessarily thought of as “early adopters”, as this will allow
for the study of impacts on access and social inclusion. Moreover, research on MaaS packages, incentives
(rewards when users display certain behaviour), the need for privacy and how to transition from
ownership models to access-based models could also provide valuable insights. By privacy, we mean
both the willingness to share data to the MaaS operator for enhanced personalisation and the willingness
to share a ride. Perhaps one of the most delicate points is the willingness to pay and costs generally,
user’s perspective. At the core, how can mobility be a service for travellers? What would truly add value
to travel generally? Do people recognise the added value of MaaS, and if not (how) can that be changed?
Further, we note that current studies about MaaS adoption and travel behaviour usually approach
respondents in a very individualised manner, yet mobility choices, like car ownership, are likely decisions
taken on the household level. Studies focusing on households as the unit of research would be desirable.
owners)/PT users, in order to better understand MaaS adoption and choices within MaaS. Segmentations
MaaS pilots. MultipleMaaSpilotsandinitiativesexist,yetfewndingsareavailabletothepublic,partly
due to commercial interests. In order to build a solid base of evidence, more MaaS pilots must be
undertaken, with a systematic impact assessment available to the general public. A tentative effort to
a geographical basis (e.g. pilots in certain regions), but also on a certain situational basis, such as for
their second cars.
Shared mobility modes and public transport. Therearegreatexpectationsforsharedmobilitymodesas
an access-based system. However, doubts persist about the reliability of such modes (e.g. availability,
transfers), their impact (congestion, modal split) and their synergy. More research on these topics is
do not yet know much about urban DRT. Arguably, the integration of shared mobility modes and private
modes, and public transport and shared mobility modes, is relevant in MaaS, yet research of these topics
is still lacking. As for PT, it is often called the backbone of MaaS, but it too seemingly requires further
study, using quantitative evidence, to determine if/when such a backbone is (always) the best option.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 41
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KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 51
Based on a literature review of peer-reviewed studies on all aspects of MaaS, Jittrapirom et al. (2017)
proposed nine core characteristics of MaaS. These core characteristics are (in no particular hierarchical
1 The integration of transport modes, in which multiple modes are combined in one single platform,
thereby allowing users to take trips using multiple modes. These modes can be both traditional
modes (public transport, private cars and bicycles) and shared mobility modes.
2 The tariff option, i.e. the fact that MaaS platforms offer a choice between pay-as-you-go and mobility
packages (containing certain amounts of kilometres-minutes-points that can be used for travelling in
3 Asingleplatform,whereuserscanplan,book,payforandgetticketsfortheirtrips,aswellasnd
real-time information.
4 Multiple actors, from customers and providers to platform owners, data management companies,
and authorities amongst others, because MaaS is built on the interaction between such various
5 The use of technologies, because MaaS relies on smartphones, Internet networks, ICT and data
6 Demand orientation, as MaaS is a user-centric paradigm seeking to offer tailored solutions to users.
7 Registration requirement, which both facilitates use of the service and allows for customisation.
8 Personalisationthatensurestheneedsofusersaremetmoreefciently.Travelhistoryandexpressed
preferences serve to provide tailored recommendations.
9 Customisation, enabling users to modify the offered option based on their preferences.
These core characteristics can be translated into relevant research themes pertaining to travel
preferences and behaviour. Given that the supply of shared mobility modes has grown in the past
topics, some of which are common to multiple core characteristics.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 52
 TableA.1 Core characteristics of MaaS and relevant themes pertaining to travel behaviour and preferences.
CorecharacteristicsofMaaS Relevantthemesfromtheangleoftravelpreferencesandtravelbehaviour
Integration of transport modes Shared mobility modes and travel behaviour/preferences
Mobility integration and travel behaviour/preferences
Tariff option Mobility integration and travel behaviour/preferences
One platform ICT (esp. mobile/tablet applications) and transport behaviour
Mobility integration and travel behaviour/preferences
Multiple actors Mobility integration and travel behaviour/preferences
User of technologies ICT (esp. mobile/tablet applications) and transport behaviour
Demand orientation ICT (esp. mobile/tablet applications) and transport behaviour
Registration requirement ICT (esp. mobile/tablet applications) and transport behaviour
Personalisation ICT (esp. mobile/tablet applications) and transport behaviour
Customisation ICT (esp. mobile/tablet applications) and transport behaviour
Mobility integration, travel behaviour and preferences,
ICT and travel behaviour; here, we mainly focus on applications,
Shared mobility modes, travel behaviour and preferences.
Thesethemeswillbeexploredseparatelywithrelevantliterature;seesections3.2, 3.3 and 3.4.
From these nine core characteristics, the user orientation is quite clear. According to Jittrapirom et al.
(2017), a number of studies argue that the strategic goal of such intense user orientation is to achieve
more sustainable transport patterns by providing people with personalised alternatives to private cars
(Chowdhury & Ceder, 2016; Giesecke et al., 2016; König et al., 2016). Consequently, car ownership, and
the willingness to shift from the car ownership paradigm, are other relevant themes to address in this
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 53
The literature review in this section is based on a selection of studies following multiple criteria.
In June 2017, Utriainen and Pöllänen (2017) searched for “Mobility as a Service” in both the Scopus
In Scopus, they found 37 papers containing the term either in their titles, abstracts or keywords.
Just under a year later that number had increased to 61. In ScienceDirect, the researchers found 33 peer-
more papers published in early 2018 than in any other previous year. Since our literature study focuses
on shifts in travel preferences and travel behaviour with MaaS, we searched the same databases three
Query 1: “Mobility as a Service” and “travel behaviour” (or “travel behaviour”). This yielded 11 papers
in Scopus (four of which are conference papers), and 19 journal articles in ScienceDirect. Three papers
were found in both databases, hence 27 unique papers were found with this query.
Query 2: “Mobility as a Service” and “travel preference”. This yielded no papers in Scopus and
two journal articles in ScienceDirect, one of which having already appeared in the previous query.
This query therefore found one unique new paper.
Query 3: “Mobility as a Service” and “modal shift”. This yielded one journal article in Scopus that
had already appeared in Query 1, and 13 journal articles in ScienceDirect, of which four had already
appeared in previous queries. This query therefore found nine new papers.
MaaS; these papers primarily deal with perspectives beyond the scope of this study, or MaaS and users
four remaining relevant papers. Because four studies are not enough for a literature review, forward and
backward snowballing techniques are used and applied to the four selected papers. To broaden the scope
even more, forward snowballing was also applied to some of the 33 other relevant papers; in particular,
those dealing with perspectives within the scope of our research were used as starting points for forward
snowballing. The snowballing techniques are described in Van Wee and Banister (2016). Kitchenham
and Charters (2007) consider these techniques as useful additions to systematic database searches.
four additional papers, of which three are overlapping. Note that, due to the limited amount of peer-
reviewed research found, we decided to include four non-peer-reviewed studies in the selection, using
popular for studying the potential impacts of MaaS. A third is a study only available via a website, but is
included because it is one of the only sources for results of an Austrian MaaS pilot. And the fourth study
contains 14 studies and is detailed in Table B.1. The type of study (conference paper, journal article,
other) is indicated, as are the main techniques used for gaining insights into MaaS and potential users.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 54
 TableB.1 Results from the systematic literature search of Mobility as a Service and its potential impacts on travel preferences
and behaviour, conducted in May 2018. Listed in order of appearance in the systematic search.
Year Authors Typeofpaper Typeofstudyandresearch
2018 Smith, Sochor and Karlsson Journal article Development of MaaS
scenarios through interviews
West Sweden x x
2016 Karlsson, Sochor and
Journal article EvaluationofaMaaSpilot
(qualitative and quantitative).
Gothenburg (Sweden) x
2016 Strömberg,Rexfelt,Karlsson
and Sochor
Journal article Comparative analysis including
a MaaS pilot.
Gothenburg (Sweden) xxx
2015 Sochor, Strömberg and Karlsson Journal article EvaluationofaMaaSpilot
(qualitative and quantitative)
Gothenburg (Sweden) x
2017 Ho, Hensher, Mulley and Wong Conference
on MaaS monthly bundles.
Sydney (Australia) x x
2017 Alonso-Gonzáles, Van Oort,
Cats and Hoogendoorn
on mode choice.
Amsterdam (The
2016 Sochor, Karlsson and Strömberg Journal article EvaluationofaMaaSpilot
(qualitative and quantitative)
Gothenburg (Sweden) x x
2018 Strömberg, Karlsson and
(qualitative and quantitative)
Gothenburg (Sweden) x x
2018 Matyas and Kamargianni Journal
on MaaS monthly bundles.
London (UK) x
2017 Haahtela and Viitamo Conference
MaaS through a survey and
focus groups (qualitative and
Finland x
2018 Kamargianni, Matyas, Li and
Other: Report Survey (attitudinal research). London (UK) x
2017 Ratilainen Other: Master
on MaaS monthly bundles.
Helsinki (Finland) x
2015 Smile mobility Other: Report
(website page)
(qualitative and quantitative).
Vienna (Austria) x
2017 Karlsson, Sochor, Aapaoja,
Other: Report Impact assessment of MaaS,
focused on in-depth
evaluations of Smile and UbiGo.
-x x
1: Query 1
2: Query 2
3: Query 3
4: Forward Snowballing (studies with citations to at least one the four original papers)
* When this literature study was conducted, this journal paper had not appeared yet. A conference paper from
the 97th Annual Meeting of the Transportation Research Board in Washington from the same authors and
with similar results was used.
KiM Netherlands Institute for Transport Policy Analysis | Mobility as a Service: a literature review 55
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... This section reviews related research on the adoption and usage of MaaS and its consequences for the environment. Much of recent research on MaaS has focused on potential target groups, their interest in MaaS (Alonso-González et al., 2020;Caiati et al., 2020;Durand et al., 2018;Fioreze et al., 2019;Zijlstra et al., 2019), and their preferred MaaS bundles Guidon et al., 2020;Ho et al., 2020Ho et al., , 2019Jang et al., 2020;Matyas and Kamargianni, 2018;Reck and Axhausen, 2020;Vij et al., 2020). These studies have used literature reviews, stated preference experiments, and models such as latent class models and latent variable models to analyze the data. ...
... Concerning the adopters of MaaS, Durand et al. (2018) systematically reviewed the literature and reported that the first groups to adopt MaaS are likely to be young to middle-aged people living in urban areas. Conversely, Fioreze et al. (2019) argued that it is not necessarily the demographic characteristics such as age that drive the interest in the adoption of MaaS, but the travel behavior. ...
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... The goal of the statements is to understand respondents' preparedness to use on-demand mobility services. In investigating the drivers of MaaS and Flex adoption, Alonso-González, et al. (2020a, b, c) used three groups of attitudinal statements, categorized by Durand et al. (2018) into: (1) Mobility integration, (2) Shared mobility modes and (3) Mobile applications. While the goal of this research is to better understand Flex-readiness, a similar setup of attitudinal statements is used, as there are many similarities in the willingness to use of MaaS and on-demand mobility. ...
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Full-text available
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Full-text available
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Full-text available
The role of governments in the regulation of potentially beneficial low carbon practices, such as car sharing, has proved difficult, as there are many different actors involved and as existing practices can be undermined. The mobility sector provides clear evidence of these dilemmas, as a wide range of users need to be engaged in the discourse over the innovations, and as existing governance structures may be unsuitable for addressing both the opportunities and limitations of innovation. This paper focuses on the sustainability implications of shared mobility and the need for new approaches to governance. A qualitative study of car sharing in London is used to examine the ideas, incentives, and institutions of the key actors involved in this sharing sector. The elements of change and continuity in the emerging sharing economy indicate the different possibilities for enhancing sustainable mobility. Any search for an alternative governance regime should take account of the ideational factors that would require an understanding of the different incentives needed to accommodate the full range of actors involved with the sharing economy.
Over the past years a substantial amount of studies has indicated that travel satisfaction is affected by a wide range of elements such as trip duration, travel mode choice and travel-related attitudes. However, what is less explored is that this travel satisfaction is not only an outcome of travel-related preferences and choices, but that travel satisfaction can also be a predictor of travel-related components. In this conceptual paper we tend to fill the gaps in the existing − albeit rather fragmented − literature concerning travel satisfaction. We provide an overview of the elements explaining travel satisfaction, and possible outcomes of travel satisfaction, with a focus on (i) subjective well-being, (ii) travel mode choice, (iii) travel-related attitudes, and (iv) the residential location. Furthermore, we suggest a continuous cyclical process including the four above mentioned elements in which travel satisfaction plays an essential role; a process which can result in the formation of travel habits.
Given the innovative nature of Mobility-as-a-Service (MaaS), various uncertainties are surrounding the possibilities for implementing MaaS. This includes uncertainties about alternative MaaS-system functionalities, about how the implementation of alternative MaaS systems might affect the overall transport system performance and about the preferences of stakeholders regarding alternative MaaS system implementation strategies. This paper contributes to this niche by collecting expert opinions about these uncertainties, using the Delphi method. The expert panel expected a fully-integrated MaaS to start operating in urban areas before 2020 and to expand to rural areas and nationally within the period of 2020–2030. In contrast to the common expectation that MaaS will attract regular car driver from their vehicles, our panel expected youth, current public transport users, and flexible travellers to be early adopters of MaaS. Transport operators are seen as the most important actors and the most preferred MaaS service integrator. Local authorities are expected to have an important role in enabling MaaS. The main objectives for implementing MaaS are to reduce car dependency and to provide a flexible and more customised transport system accessibility to the general public. The implementation of MaaS as a pilot project is considered the most preferred policy in the next phase. These findings largely support earlier reported findings on MaaS implementation. This study report new findings regarding the levels of consensus and how the experts changed their individual opinions in light of the group results on the studied topics. Regarding certain topics, such as the early market, there are higher levels of agreements among the panel with lower proportions of them changing their selections in light of the group results. Whereas in other topics, such as planning for future implementation, the level of agreement are lower with higher proportions of experts changing their selections. These two attributes can be combined to infer how certain the panel is on the topics studied. The study also provides new insights into the possible vulnerabilities and opportunities that can arise in relation to MaaS implementation, the associated levels of importance and uncertainty, and the possible responding actions. The experts also identified potential social issues and challenges in scaling-up the pilot. The findings of this study are of interest to practitioners and researchers in the field of MaaS planning and can be used to initiate a discussion among actors and stakeholders to formulate implementation plans for different MaaS concepts.
On-demand ride services, such as those offered by Uber and Lyft, are transforming transportation supply and demand in many ways. As the popularity and visibility of Uber/Lyft grow, an understanding of the factors affecting the use of these services becomes more important. In this paper, we investigate the factors affecting the adoption of on-demand ride services among millennials (i.e. young adults born between 1981 and 1997), and members of the preceding Generation X (i.e. middle-aged adults born between 1965 and 1980) in California. We estimate binary logit models of the adoption of Uber/Lyft with and without the inclusion of attitudinal variables, using the California Millennials Dataset (N = 1975). The results are consistent across models: we find that highly educated, older millennials are more likely to use on-demand ride services than other groups. We also find that greater land-use mix and regional accessibility by car are associated with greater likelihood of adopting on-demand ride services. Respondents who report higher numbers of long-distance business trips and have a higher share of long-distance trips made by plane are also more likely to have used these services, as are frequent users of smartphone transportation-related apps, and those who have previously used taxi and carsharing services. Among various attitudinal factors that were investigated, individuals with stronger pro-environmental, technology-embracing, and variety-seeking attitudes are more inclined to use ridehailing. These findings provide a starting point for efforts to forecast the adoption of on-demand services and their impacts on overall travel patterns across various regions and sociodemographics.
Kutsuplus was a novel, flexible micro transit service (FMTS) operating in Helsinki during 2012 to 2015. The service included a range of new technological development, ranging from routing algorithm to marketing and user interface. However, at the end of 2015, the service ceased due to budgetary constraints. In the context of service discontinuation, and the lack of in-depth understanding of user perspectives about urban FMTS, this paper aims to uncover the perspectives of the users of the service, users that discontinued using the service during its operation, and persons who did not use the service. The methodological approach is based on a questionnaire, with mapping capabilities enabling collection of georeferenced data. Questionnaire results are validated using actual Kutsuplus trip analysis. The results show that Kutsuplus users were a diverse group both when considering socio-economic status and travel behavior. In addition, the results include detailed analysis of stated trip characteristics, including spatial analysis of trip origins and destinations. Furthermore, the results include qualitative analysis of respondents' opinions and recommendations about positive and lacking FMTS features. The paper ends with a summary of positive Kutsuplus features, followed by the discussion of aspects for future deployment, including end-user and service area analysis, marketing strategy, and service usability. Finally, the paper provides recommendations for further research on FMTS.
Bundled offerings that facilitate using multiple means for solving everyday travel needs are proposed to hold potential to facilitate a modal shift from private cars to servitized transport modes, including public transport (PT). This type of offering, often coined Mobility as a Service (MaaS), may require new forms of partnerships, in which private actors play a larger role in the creation of public value. Accordingly, based on input from 19 interviews with MaaS actors active in West Sweden, this paper explores how MaaS could develop and how PT might be affected. Three predictive scenarios are identified – market-driven, public-controlled and public-private – and the implications for future PT, in terms of the scope, usage, access, business model, competence structure and brand value, are discussed in relation to these. The authors conclude that finding a regulatory ‘sweet spot’ that drives innovation and secures public benefits will be key for future developments.
Traffic congestion continues to be the bane of many metropolitan areas and has exercised the minds of experts for at least the last 60 years. With the advent of smart (intelligent) mobility, aligned with digital disruption and future connected and collaborative transport including extensions to autonomous vehicles, the question of whether we have a new window of opportunity to tame congestion is now high on the list of possibilities. It is however very unclear what the future will look like in respect of congestion on the roads, especially if we rely on 'smart' technology and continue to reject reform of road user charging and new opportunities to fund the sharing model. This paper looks at a number of themes as a way of highlighting possibilities and challenges and promotes a position that congestion may not be reduced, especially without a significant switch to the sharing economy and relinquishing of private car ownership; the urgent need for government to define the institutional setting within which smart mobility can deliver reductions in congestion; and the crucial role that road pricing reform must play to ensure that those who benefit (suppliers and travellers) contribute to pay for the infrastructure (in particular) that they gain benefit from.