Using, Sharing, and Owning Smart Cars
A Future Scenario Analysis Taking General Socio-Technical Trends into Account
Christina Pakusch, Paul Bossauer, Markus Shakoor and Gunnar Stevens
Department of Management Sciences, Bonn-Rhein-Sieg University, Sankt Augustin, Germany
Keywords: Megatrends, Foresight, Scenario, Trend Analysis, Shareconomy, Ownership, Usership, Digitalization, Self-
Driving Cars, Mobility as a Service.
Abstract: The megatrends towards both a digital and a usership economy have changed entire markets in the past and
will continue to do so over the next decades. In this work, we outline what this change means for possible
futures of the mobility sector, taking the combination of trends in both economies into account. Using a sys-
tematic, scenario-based trend analysis, we draft four general future scenarios and adapt the two most rele-
vant scenarios to the automotive sector. Our findings show that combing the trends from both economies
provides new insights that have often been neglected in literature because of an isolated view on digital
technology only. However, service concepts such as self-driving car sharing or self-driving taxis have a
great impact at various levels including microeconomic (e.g., service and product design, business models)
and macroeconomic (e.g., with regard to ecological, economical, and social impacts). We give a brief out-
line of these issues and show which business models could be successful in the most likely future scenarios,
before we frame strategic implications for today’s automobile manufacturers.
1 INTRODUCTION
What are possible futures of car mobility in Europe
2030-50 and what are the implications at the con-
sumer, business, and societal levels?
In various respects, modern Western societies are
mobile societies characterized by highly individual-
ized lifestyles. This mobility is facilitated by
transport systems and mobility, with the car as the
main means of transport. However, the picture is
changing as monomodal, private-car based mobility
neither meets the challenges of today`s mobility
complexity nor satisfies the needs of individualized
lifestyles and the demands of sustainable societies.
In contrast, multi-optional offers where users can
combine appropriate mobility forms that suit their
respective situations seem to be better suited. Com-
puter-based and app-based travel information sys-
tems make it easier to plan and perform these mul-
timodal trips. First signs are already visible; in car-
focused nations such as Germany the importance of
public transport and non-motorized transport slightly
increased in recent years (Lenz et al. 2010).
New mobility concepts such as fully autonomous
driving are appearing on the horizon. Self-driving
cars, in particular, do not present just an incremental
innovation in safety and fuel-efficiency. They pre-
sent a completely new mode of transportation that
has the potential of a disruptive innovation (Milakis
et al. 2015). They enable completely new mobility
services, which affects the choice and use of availa-
ble transportation options.
The research field of self-driving is fairly new.
Most of the work focusses on technological, legal,
political, and ethical issues. Only a few papers in-
vestigate the design of mobility services and us-
ership models and their impact on everyday mobility
(cf. Section 2). This blind spot is partly caused by
the fact that automated driving is currently not yet
reality and its effects are not yet empirically observ-
able. Investigations into a self-driving-based mobili-
ty are therefore, to some extent, uncertain and specu-
lative. However, to actively shape the future, we
have to envision possible effects of this trend. Mo-
bility researchers, traffic planners, and business men
should take the opportunity to re-think mobility from
scratch and develop urban concepts and business
models that go beyond switching from private tradi-
tional cars to private autonomous cars.
We study possible future development paths by
using scenario-based analysis. Supplementing exist-
Pakusch, C., Bossauer, P., Shakoor, M. and Stevens, G.
Using, Sharing, and Owning Smart Cars - A Future Scenario Analysis Taking General Socio-Technical Trends into Account.
DOI: 10.5220/0005960900190030
In Proceedings of the 13th International Joint Conference on e-Business and Telecommunications (ICETE 2016) - Volume 2: ICE-B, pages 19-30
ISBN: 978-989-758-196-0
Copyright
c
2016 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
19
ing scenario studies (Epprecht et al. 2014; e.g. Lit-
man 2014; Milakis et al. 2015), we take a closer
look at the general social megatrends of digitaliza-
tion and usership rather than ownership. We outline
how these two megatrends affect the future of car
mobility. In particular, we believe that combining
both trends constitutes the disruptive quality that
impacts the consumer, business, and social levels.
Although our analysis shows that it is a megatrend,
usership is unlikely to become the dominant con-
sumption mode. Business models and policy instru-
ments should therefore be designed for the situation
that owning and using smart cars will co-exist for a
long period.
2 RELATED STUDIES
In the last years, the smart car research field has
witnessed a boost in work covering topics such as
driver assistance systems, connected cars or auton-
omous, self-driving, or driverless vehicles. Several
studies have focused on particular technological
issues while others pinpoint to ethical issues and the
user acceptance of self-driving cars. Based on these
insights, some studies looking at the future have
been published recently. They draft scenarios that
show how automated vehicles might change future
mobility; work that we continue here.
One cluster of future studies focusses on policy
instruments and their impact on the penetration rate
and speed of adoption. For instance, Milakis et al.
(2015) discuss different development paths in the
Netherlands with regard to the speed at which auto-
mated vehicles are accepted. They assume that tech-
nological development and policy directions are the
most relevant driving forces. In their scenario, fully
automated cars are most likely to be launched be-
tween 2025 and 2045, penetrating the market rapidly
after their introduction. Litman (2014) also factors
policy instruments into his discussion of various
paths with regard to market penetration and diffu-
sion of other technological innovations. For his most
realistic scenario, he concludes that it will take 10-
30 years from market launch until the automated
vehicle dominates car sales. In a similar vein, Nieu-
wenhuijsen (2015) outlines a simulation model that
also considers policy instruments such as knowledge
sharing, collaborative projects, and public and pri-
vate technology funding. His model shows that these
instruments lead to faster technological progress and
hence to a faster market penetration. Yun et al.
(2014) ascertain that decreasing governmental regu-
lation and an increasing business model level will
facilitate market growth. Their findings are based on
a simulation that shows how different technology
paths and business models impact the market devel-
opment of automated vehicles under varying cir-
cumstances.
A second cluster of studies focusses on human
factors and their impact on business strategies. For
instance, Bartl (2015) shows that strategic planning
should consider vehicle design and ownership as
relevant dimensions that shape car futures. The first
dimension ranges from conventional to reinvented
design, depending on the level of automation. The
second dimension is characterized by two poles:
owning versus sharing. Similarly, Epprecht et al.
(2014) use expert interviews to identify automated
driving and sharing as two visionary forces in the
automotive industry. Conducting a scenario analysis,
they pinpoint that the user acceptance of car-sharing
and usership models will be a key question in the
future. In particular, they see current consumer atti-
tudes as a vital barrier to the success of innovative
technologies.
This barrier has led to a third cluster of user ac-
ceptance studies recently gaining more attention.
With regard to autonomous cars in general, a recent
study by (Payre et al. 2014) reveals that a large ma-
jority of the population have a positive attitude and
can imagine buying and/or using them. The litera-
ture further shows that acceptance depends on sever-
al other parameters. For instance, acceptance in-
creases when users are allowed to take control (EY
2013). Other factors are age and gender, individual
personality, pre-experience with partly autonomous
cars, characteristics of the innovation, the driving
environment, and the manufacturer’s reputation
(Nordhoff 2014; Rödel et al. 2014). At the same
time, other studies report that people are concerned
about self-driving vehicles (Howard and Dai 2014).
These concerns seems to be cultural and country
dependent (Schoettle and Sivak 2014) as well as
gender dependent: females seem to be more con-
cerned than males (Schoettle and Sivak 2014).
However, most studies focus on autonomous cars
in general but neglect ownership as a relevant cate-
gory. In particular, the surveys do not differentiate
between ownership and usership models but focus
on private cars only – whether explicitly or implicit-
ly. Only a few investigations look at self-driving
mobility services, e.g., self-driving taxis, in detail
(e.g.,(Burns et al. 2013; Hars 2015). Furthermore,
empirical studies can only provide a snapshot of the
status quo; they fail to consider the long-term pro-
cess of changing norms and attitudes, changes that
affect user acceptance in the long run.
ICE-B 2016 - International Conference on e-Business
20
In summary, the literature shows that technologi-
cal development paths cannot be studied in isolation
because they are shaped by various socio-technical
factors. These factors include ethical and legal issues
as well as economic and design issues. All in all, it is
the consumer who will determine what kind of mo-
bility will dominate, and ownership would thus
appear to be a category that future mobility studies
should take into account. User acceptance can be
investigated in empirical studies but only for current
users; researchers are unable to consider temporal
changes in user attitudes. We therefore want to an-
swer two research questions in this work:
(RQ1) What are the pre- and post-conditions of the
broader socio-technical trends of digitalization and
usership?
(RQ2) How do these trends impact future car mobil-
ity models?
3 METHODOLOGY
To answer our research questions we conduct a
scenario analysis. This methodology is an approved
instrument for identifying and structuring changes,
drivers, and consequences within unknown, uncer-
tain, and changing environments (Mahmoud et al.
2009; Ringland and Schwartz 1998). Various scenar-
io analysis techniques exist. In this paper we adapt
the scenario-axes technique (van ’t Klooster and van
Asselt 2006). This variant covers the four activities:
scanning, monitoring, forecasting, and assessing in
order to outline possible futures.
We applied these steps as follows: First, we out-
lined the framing question (at the beginning of this
paper), which was shaped by the current car mobility
discourse in research, politics, and the mass media.
We reviewed general future studies and found that
the two megatrends of digitalization and usership
economies are often mentioned in literature (Berger
2013; Mont et al. 2014). Hence, we analyzed these
megatrends in more detail by placing them into a
broader context of general trends in societies without
applying them to a specific industry at this point of
the analysis. We then identified the pre-conditions
that have driven the two trends so far, taking rele-
vant literature into account. Post-conditions under
which the trends are going to proceed were also
investigated. The assumptions behind these post-
conditions were subsequently evaluated with regard
to their uncertainty and their impact on the trend.
This evaluation process was adapted from the con-
cept of expert assessments. To increase the evalua-
tion’s intersubjectivity, three authors independently
rated the impact of the assumption. In most cases,
the evaluations coincided with little deviation. When
there was a higher deviation, the authors discussed
their opinions and came to a consolidated conclu-
sion. Based on the results of this evaluation, the two
most critical and thus decisive driving forces were
derived by selecting the most uncertain assumptions
with the highest impact to the trend (van ’t Klooster
and van Asselt 2006), also taking into consideration
other important assumptions. These critical uncer-
tainties serve as the axes for the scenario matrix that
classifies the four scenarios. By taking into consid-
eration the assumptions made for the trends and
fitting them into the context of the particular scenar-
io, coherent scenario descriptions were developed.
Finally, we evaluated the scenarios’ probabilities, by
using the method we applied in evaluating the post-
conditions, selected the most likely scenarios, and
interpreted them in terms of car mobility futures.
Based on the scenarios implications for the industry
were derived on a consumer, business, and social
level.
4 TRENDS
4.1 Digitalization
Pre-Conditions
Digitalization describes the socio-technological
trend of the ubiquitous computing of all areas of life
in which people are part of digital ecosystems using
smart objects that are mutually connected without
loss of information or function (Weiser 1991).
The main driver of this trend is the exponential
growth of IT-technology, which can be seen, for
instance, in the doubling of the computing power
every 18 months (Moore’s Law), in the doubling of
data transfer rates every six months (Gilder’s Law)
or in the value of computer networks being propor-
tional to the square of the number of users and ma-
chines (Metcalfe’s Law) (Laudon and Laudon 2012).
This development is supplemented by widespread
utilization, general user acceptance, and everyday
usage of social web and digital services. Today it is
common to have a smart phone and a Facebook
account, to buy goods online, or to use location-
based services such as Yelp or Foursquare. With the
development towards an Internet of Things (Atzori
et al. 2010), various systems are becoming increas-
ingly integrated, with social webs, semantic webs,
and sensor webs constituting dynamic, cyber-
physical systems. Material goods are enriched by
Using, Sharing, and Owning Smart Cars - A Future Scenario Analysis Taking General Socio-Technical Trends into Account
21
digital solutions and becoming cyber-physical. Em-
bedded systems are an integral part of products and
services, leading to new or expanded feature sets.
These changes are the result of the progress in artifi-
cial intelligence (AI) and semantic technologies,
which have allowed goods to become smarter and
more autonomous.
Digitalization has already changed entire indus-
tries within the consumer market. It has led to a
whole industries being rapidly transformed, with
products and services completely or partly been
substituted by digitized ones (Svahn and Hen-
fridsson 2012). Examples can be found in the music
industry (Huang 2005), the photography industry
(Lucas and Goh 2009), and the newspaper industry
(Karimi and Walter 2015).
Post-Conditions
For this trend to proceed, it is important to assume
continuing technological advancement. Technolog-
ical progress cannot be expected to stagnate. Gov-
ernment investments in and subsidization of Inter-
net and mobile infrastructure build a base for further
networking and for developing the artificial intelli-
gence of things. In all probability, governments are
going to implement regulations to improve Internet
security and personal privacy and thereby reduce
cybercrime and terrorism to a minimum. Further
they will define requirements for secure information
systems and clarify liability questions within auton-
omous systems. They will also continue to outline
competition regulations and improve the funding of
open standards, making connection of devices and
system integration easier.
People’s trust in digitalized environments will
continue to grow, and they are prepared to connect
their goods and use smart functions in many areas of
their everyday life. It can be safely assumed that, as
long as the data is not too sensitive, people will be
ready to supply private data to benefit from the con-
venience these goods provide. The generation con-
nected, or so-called generation c (Friedrich et al.
2011), born after 1990, has grown up or will grow
up in a primarily digital world. Their familiarity with
technology and reliance on mobile communications
and their desire to remain in contact with large net-
works, either private or business ones, will change
how everyone works and how they consume.
4.2 Usership
Pre-Conditions
Usership (Nieuwenhuijsen 2015) describes the so-
cio-cultural trend of sharing or using goods on de-
mand rather owning them (Belk 2007). In the litera-
ture, these two trends of sharing and using on de-
mand are often described independently (Malhotra
and Van Alstyne 2014; Scholl 2006). In this paper,
we consider usership to cover both the using and the
sharing concepts.
There are different drivers for this trend. First, in
the past, ownership had a strong symbolic function,
following the dictum “You are what you own” (Belk
1988). But in times of mass-consumption and rising
urbanization, owing has lost its means of distinction.
As a result, the attitude has shifted in recent years
towards alternative forms of property and consump-
tion (Hamari, Sjöklint, and Ukkonen 2015). Second,
increasing environmental awareness is driving us-
ership. Here, sharing resources is not tainted by an
image of poverty; it now has a positive green image
(Botsman and Rogers 2011; Hamari et al. 2015; Tils
et al. 2015). Moreover, sustainable consumption
serves as a new means of distinction (Soron 2010).
Third, the Internet is often seen as enabler for
collaborative consumption services (Sundararajan
2013) as it reduces tremendously the searching and
transaction cost of sharing goods and helps to reduce
physical interaction. Web 2.0 created yet more forms
of sharing (Belk 2014) since the sharing platforms
allow suppliers to reach a broader audience and
consumers to have access to a broader range of
products and services at minimal costs. The trend
towards usership is most evident in the case of im-
material goods such as music, films, or software,
where owning has increasingly become the excep-
tion rather than the rule (Cusumano 2014).
Post-Conditions
Generally, new sharing and service concepts are
well known, but they currently play a minor role in
people`s everyday life. However, it can be assumed
that they will become a general commodity. In par-
ticular, the young generation (generation c) is chang-
ing its consumer habits (Heinrichs and Grunenberg
2012). The general assumption is that consumer
awareness of sustainability issues will continue to
expand. This assumption is supported by an increas-
ing consumer demand for sustainable goods and
food. Further, international agreements such as the
United Nations Climate Change Conference 2015
agreed to a strict set of goals limiting global warm-
ing. Hence, it is reasonable that sustainable transport
modes will be widely promoted by governments in
the future. A general abundance of goods and gener-
ation c, which embraces the shared economy-
thought, may allow a shift in consumer attitude
from ownership for status reasons to usership to
ICE-B 2016 - International Conference on e-Business
22
develop. The growing population in conjunction
with limited resources will inevitably result in higher
costs for consumers. Hence there will be a need to
forgo individual ownership. The question is in which
categories of goods the shift will take place next.
It can further be assumed that the transaction
costs of service and sharing economies will decrease
because of an increasing urbanization (Un-habitat
2010). The higher density of people in urban will
make sharing easier to realize because more poten-
tial users will be able to collaborate in sharing. Ad-
ditionally, it will become necessary to share goods in
some sectors with limited (mineral) resources e.g.,
rare earth elements used in the production, but also
with limited physical resources such as housing,
streets, or parking places. Under the assumption that
the governments will set clear regulations concern-
ing privacy issues as well as clear regulations, e.g.,
for liability standards, occupational safety and taxa-
tion, consumers are more likely to be more open to
using and sharing, and will thus strengthen the trend.
Due to their contribution to sustainability, govern-
ments will presumably promote and subsidize col-
laborative consumption.
4.3 Impact Evaluation
The evaluation process has already been discussed in
more detail in Section 3. From the evaluation, we
were able to identify five driving forces (see Table
1). Each is assumed to be critical, with either a direct
or an indirect effect on how the trends continue
and/or intensify.
Table 1: Evaluation of Post-Conditions.
Post-Condition
Potential
Impact
Uncer-
tainty
Total
Digitalization
Technology 7 2 9
Regulations 5 4 9
Investments 8,5 3 11,5
Connection 8,5 6
14,5
Gen-C Attitude 7 2 9
Usership
Sustainability 4,5 4,5 9
Consumer Attitude 9,5 7,5
17
Costs 7,5 1,5 9
Urbanization 7 3 10
Regulation 6 5 11
To assess the level of impact, we considered the
post-condition of each factor and how it shapes
future developments. To assess the critical uncer-
tainties, we stated how confident we are that each
particular condition will come true. By combining
both indicators, we could define the critical condi-
tions/uncertainties (Total in Table 1). For the digital-
ization trend, we conclude that the actual develop-
ment path of the Internet of Things connecting
cyber-physical systems (Atzori et al. 2010) is crucial
and builds the first critical uncertainty. For the us-
ership trend, we conclude that the acceptance of
usership models is primarily dependent on a change
in consumers’ attitudes. Usership will only become
a dominant economic model in society if ownership
becomes less important for consumers.
5 SCENARIOS
Our scenario development reflects that these two
trends play the most vital role in how the future will
develop; connected smart systems and usership
attitudes therefore build the axes of the scenario
graph. The combination of these two different driv-
ing forces with their reasonable possibilities leads to
the following set of four scenarios (see Figure 1).
Figure 1: Scenario Matrix.
5.1 Private Products
In a private products scenario, people prefer owner-
ship over usership for goods that are not highly
digitally connected. Status symbols are still essential
for individuals, even if the goods that provide this
status have changed. The importance of expressing
one`s individuality through those goods results from
increased costs caused by a rising population in
conjunction with limited resources. The growing
urbanization and a slow but steadily growing aware-
ness of sustainability needs also contribute to higher
costs. At the same time, only a few of these goods
are integrated, although technological progress has
made a broader networking of things possible. But
since the high complexity of this market does not
allow the government to provide rigorous openness,
security, and privacy standards and since data abuse
and cybercrime occur, people are not ready to hand
over personal and sensitive data.
Using, Sharing, and Owning Smart Cars - A Future Scenario Analysis Taking General Socio-Technical Trends into Account
23
5.2 Pay per Use
In this scenario, people have a usership attitude.
They use and share things instead of buying and
owning them. The attitude is supported by people
recognizing and accepting the need to reduce waste
and environmental pollution. This consumer behav-
ior is also encouraged by the government: the gov-
ernment has set strict climate protection goals and
promoted the usership economy by increasing the
price of ownership, formulating minimum require-
ments for shared goods and services, and developing
strict data protection laws. Indeed, a high connection
and integration of the shared goods and services is
possible from a technological point of view, but
techniques reach their limits when it comes to ethi-
cal questions that a machine is not able to answer.
Since people additionally have data protection con-
cerns, society often rejects further connection such
as smart services and smart goods.
5.3 Smart Products
In the smart product scenario, the vision of an Inter-
net of Things (Atzori et al. 2010) where all things
are smart and connected has become real. This sce-
nario promises great technological progress, a plat-
form for digital innovations, and high security and
privacy standards. People set great value on sustain-
able assets. However, as in the private products
scenario, people prefer owning rather than sharing
goods, with a preference for high-tech products as
status symbols. In the private domain, more and
more appliances and devices are communicating and
that is leading to a smart environment. In particular,
smart technologies are used when they make domes-
tic life more convenient. People are ready to trust
technology within their ownership. However, they
are still sceptical towards digital, connected services
where personal data are collected and externally
used by commercial and public service providers.
Smart connections are only tolerated if they increase
comfort and do not affect the power of disposition
and the privacy of personal data.
5.4 Smart Services
As in the previous scenario, the technological vision
of an Internet of Things has become real. But here
the social vision of service and sharing economies
has also become real. Consumer attitude shifts from
an ownership to a usership approach. Status-based
thinking has been replaced by a pragmatic approach
of benefit-based thinking. Reduced power of dispo-
sition and control is tolerated if it increases quality
and stability of the overall service system and is
compensated by other incentives (e.g., service dis-
counts, service upgrading, etc.). Therefore the con-
sumer agrees to disclosing personal data if it does
not just improve the provider’s resource planning
but has a personal benefit, too. Improved efficiency
means that smart services also answer the challenges
of continued resource limits and sustainability de-
mands. Resource efficiency is not simply an option;
it is a necessity for society to prosper and advance.
Development is facilitated by an increased urbaniza-
tion, where more potential sharers are available and
sharing becomes easier and the pressure to share
increases. Sharing is supported by the government
applying share-focused policies e.g., investing in
share-infrastructure in urban areas, taking measures
to increase sharing, and imposing regulations and
standards for privacy and security. These improved
sharing conditions are internalized by consumers,
thus strengthening their usership and sharing atti-
tude. This change in attitude also leads to a greater
desire to stay connected through networks, enabled
by technology breakthroughs and government subsi-
dies in investments in high-speed broadband net-
works. The high privacy standards give society
greater trust in new technologies. Digital interactions
and collaborations replace major parts of society’s
face-to-face interactions.
5.5 Scenario Evaluation
We consider the general scenarios smart products
and smart services to be the most likely scenarios.
Likelihoods of the scenarios were evaluated by as-
sessing them for the two dimensions separately and
multiplying them for the individual cells. This step
reduces the complexity, but neglects possible inter-
actions between both dimensions.
There are good reasons for assuming an increase
in the socio-technological trend, displayed on the
horizontal axis, e.g., by the connection, integration,
and collaboration the value of the Internet of Things
growths squared for all members (Metcalfe’s Law).
However, several counterforces might hinder or
delay this trend. With the further connection of
things, the complexity grows exponentially, too.
Therefore we consider that high connectedness is
more realistic (assessed with 70% probablity) than
digital separateness (assessed with 30% probability).
For the vertical axis (usership attitude) both di-
rections are conceivable. On the one hand, a future is
possible where the material-oriented attitude remains
because of two main reasons: first, usership does not
ICE-B 2016 - International Conference on e-Business
24
provide the same level of comfort, reliability, or
control as owning goods and second, identification
with goods still matters. On the other hand, usership
economies generally have better resource efficiency.
This improved efficiency especially holds in the case
of smart services. A complete disappearance of
ownership, however, does not seem to be realistic.
We therefore assessed an expansion of the usership
attitude with 40% probability and the ownership
attitude remaining the dominant model as being 60%
probable.
Figure 2: Scenario Matrix.
Based on these assessments, we consider the
scenarios smart products (42%) and smart services
(28%) to be the ones that are most likely to occur in
the future. In contrast, non-digital private products
(12%) and pay-per-use services (18%) will be less
important in the future (see Figure 2).
6 CAR FUTURES
In this section, we apply these general consideration
to the mobility sector, in particular what this means
for possible car futures. We focus on the smart
products and the smart services scenarios as the two
scenarios with the highest probabilities. As both
have similar probabilities, we also believe that the
future of the car is given by a mixture of both sce-
narios. Hence, we also outline what a co-existence
of both could look like in the future.
6.1 Smart Private Cars
In terms of mobility, the smart products scenario
means that in the future private cars still play a ma-
jor role in people`s individual mobility. However,
future private cars are smart equipped with innova-
tive technological features. The cars are able to ma-
neuver automatically within cities and on highways.
They support drivers and provide new driving expe-
riences in various ways. Overall, this scenario de-
scribes an evolutionary development path, where
smart cars are mainly characterized by additional
features. The general concepts do not differ signifi-
cantly from those nowadays. Still, there are subtle
but important differences in detail. For better or
worse, in this scenario, owners decide individually
when to make use of the new smart features and
when not to.
On the consumer level, needs will change and
requirements will be imposed on smart cars (Litman
2014). We can distinguish between the pragmatic
values and the hedonic values a (smart) car has for a
consumer (Hassenzahl 2001). The business models
need to satisfy the following demands of car buyers.
The most important pragmatic value propositions
attributed to car mobility are autonomy, independen-
cy, and flexibility (Meurer et al. 2014), all of which
inherently apply in this ownership-oriented scenario.
A special case is linked to those who cannot drive
because of cognitive or physical constraints, such as
older or disabled people. For this user group, smart
cars are a promise of liberty (Litman 2014; Meurer
et al. 2014). Comfort is an important reason for
choosing cars as a preferred mode of transportation,
too (Shove 2003). In this scenario, smart cars aim to
gain a comparative advantage by increasing the
perceived comfort. Many smart car features fall into
this category: the highway pilot, valet parking, or
traffic jam assistant (Anderson et al. 2014; Litman
2014; Maurer et al. 2015; Milakis et al. 2015).
Reduced crashes and increased safety is another
advantage often mentioned in literature (Litman
2014; Milakis et al. 2015). From a consumer per-
spective, however, safety is less important than the
subjective feeling of safety (Beggiato and Krems
2013). Cooperative concepts that delegate control to
an external authority (such as Cooperative Adaptive
Cruise Control) might be perceived as less secure
and, as a result, be less accepted by smart car owners
(Nieuwenhuijsen 2015). Drivers must be able to
switch to (semi-) autonomous driving. On the one
hand switching it off ensures to meet the drivers’
goals of autonomy, perceived control, and perceived
safety. On the other hand switching to (semi-) au-
tonomous driving relieves of driving activities that
are perceived as annoying and wasteful. In addition
to reduced stress while driving (Litman 2014), the
value of time (Gucwa 2014) increases and smart cars
offer new work opportunities during travel.
Features such as intelligent traffic-aware routing
and adaptive cruise control are a further category
that improve driving efficiency (Baydere et al. 2014;
EC 2011; Litman 2014; Milakis et al. 2015). Here
too, such features are only accepted if they do not
Using, Sharing, and Owning Smart Cars - A Future Scenario Analysis Taking General Socio-Technical Trends into Account
25
reduce driver autonomy; they must be perceived as a
support not as a burden (Davis 1989). For instance,
cooperative concepts such as routing vehicles into
platoons (Bergenhem et al. 2012) must be optional.
It is questionable whether a driver will use this op-
tion, thus perhaps also saving a small amount of
energy, if the platoon speed is perceived as too low
(or too high in the case of insecure people).
In this scenario, the hedonic value of cars having
a symbolic function for their owners remains. They
are a means of distinction (Bourdieu 1984), express-
ing an innovative attitude, a social status, or mem-
bership of a peer-group or (sub-)culture. Other
common hedonic values attributed to cars and driv-
ing are fun (Rödel et al. 2014) and sensation seeking
(Nordhoff 2014). Here, an incentive for owning cars
is being able to tune them and steer them. Smart cars
do not necessarily preclude these options. At best,
they provide new opportunities for enjoyment and
sensation seeking, e.g., enabling more sports driving,
even for novice drivers, and providing software
updates that improve the car e.g., by making it more
powerful.
On the business level, car manufacturers must
face up to new legal restrictions and questions of
liability. For instance, they need to build up compe-
tencies in cyber-security by attracting talents from
outside the traditional automotive industry (Gao et
al. 2014) and clarify the issue of liability in the case
of an accident (Maurer et al. 2015). In addition to
traditional competitors, car manufactures have to
compete with new market entrants from the IT and
communication industry. In particular, safety and
intelligence features will benefit from digital car-to-
car and car-to-infrastructure communication. IT
companies might therefore have a comparative ad-
vantage, and major shifts in the market share might
occur. However, in this scenario, lock-in and net-
work effects are smaller than those in the IT sector.
In particular, there are too many individual demands
and preferences for them all to be satisfied by just
one brand. This implies that the private smart car
market is not a “winner-takes-all” one (Buxmann
and Hess 2015). New niche markets and market
segments will also emerge. For instance, smart cars
enter the new market segment of providing inde-
pendent mobility for non- or handicapped-drivers.
Cars in this segment reduce the need for motorists to
chauffeur non-driving family members and friends
or, for those being driven to use conventional public
transit or ridesharing services (Litman 2014; Meurer
et al. 2014). Another topic relates to brands and the
satisfaction of the symbolic value of owning a car.
Here, high-tech IT companies as well as premium
car manufacturers could benefit from strategic alli-
ances to create brand’s promises of highly innova-
tive and appealing cars with a high comfort level, a
high fun factor, and/or a high symbolic value
(Maurer et al. 2015).
On the societal level, the main problems pres-
ently caused by private car traffic compound in this
scenario. Since people are in need of a car, the num-
ber of personal cars is going to increase. Especially
in some regional areas, the growing population and
urbanization have lead to congestion, parking chaos,
and increasing air pollution. The current parking
problems remain and reach new dimensions. For the
individual, valet parking features make parking less
stressful. However, as each person wants to have a
parking place nearby, parking spaces must be in-
creasingly provided in the cities. Alternatively, to
improve the availability, smart parking might be
realized by driving around the block autonomously
until the driver is back from a (short) stop. Automo-
bile manufacturers have to face and address these
problems by taking the rising challenges into con-
sideration. Possible solutions can be the develop-
ment of self-parking cars, finding free lots or navi-
gating to centralized parking areas, or space-saving
cars such as foldable cars (Suh et al. 2013). Car
manufacturers also need to launch enhanced eco-
friendly cars, either by improving propulsion tech-
nologies using renewable energy or through ad-
vanced efficiency.
However, autonomous private cars can address
other problems. Driving safety is improved whenev-
er the car takes over control during critical traffic
situations. Governmental legislation might even
require cars to activate driving assistance systems to
ensure safe driving and that the laws are obeyed. At
the same time, automobile manufacturers face new
customer groups such as disabled or older people, or
maybe even children. These people are now able to
use their private autonomous cars independently.
6.2 Smart Car Services
In terms of mobility, the smart services scenario
means that, in future, private cars play no or only a
minor part in the daily routine. It shares with the
previous scenario that cars are smart and able to
maneuver automatically. The aim, however, is not to
support drivers but to support passengers who use
the new smart mobility services. Therefore the busi-
ness models of automobile manufacturer will change
distinctly. Car manufacturers have to go through a
revolutionary process and realign their business
models.
ICE-B 2016 - International Conference on e-Business
26
On the consumer level, individual pragmatic
needs differ from the previous scenario only in de-
gree. Perceived safety and perceived flexibility are
still important for consumers, in particular having
the freedom to go anywhere at any time. The signifi-
cant difference, however, is the attitude concerning
how the need is satisfied. Instead of owning a car,
consumers chose the mobility service optimal for the
situation (Scholl 2006). As a result, the long-term-
oriented mobility decision of buying a car shifts to a
short-term-oriented mobility decision and choosing
mobility services in line with the situation. There-
fore lock-in effects can be reduced in the use of a car
so that the transport choices are more volatile. In
particular, pragmatic values and hedonic values do
not refer to the smart car itself anymore, referring
instead to a smart service system. From the consum-
er perspective, the most important pragmatic service
qualities are availability and reliability. In addition,
the service must be easy to use without great plan-
ning (Scholl 2006) e.g., easy to book and pay for via
Smartphones. For disabled and older people, the
accessibility of the service system plays a crucial
role, for instance, that smart cars can be used with a
wheel-chair, luggage can be easily stowed, or assis-
tance is offered – either by service staff or service
roboters.
As the hedonic value of driving fun (Rödel et al.
2014) decreases in this scenario, the pragmatic de-
mand for travel time enrichment (Gunn 2001) in-
creases. Hence cars might be equipped as mobile
offices or offer special entertainment features or
opportunities for relaxation.
In this scenario, consumers become more price
conscious when the smart cars rely on a pay-per-use
model. For private cars these costs are much less
transparent as many costs such as acquisition, re-
pairs, and insurance are indirect. Therefore they
weigh up the cost and benefits of service features
with regard to the particular situation. Like today –
where people usually take buses and only take taxis
in exceptional situations – a consumer might accept
ridesharing-like smart car services when they are
significantly cheaper and only use taxi-like services
as an exception. In addition to the practical cost-
benefit analysis, selecting these service systems also
has a symbolic significance. For instance, using
ridesharing-type services expresses a green value
system. However, the use of taxi-like and exclusive
transport services might serve as status symbol
(Scholl 2006).
On the business level, the business models aim
to satisfy the outlined demands of mobility service
users. Producing and selling cars to private custom-
ers will no longer be the prevailing business activity.
Instead one promising business model lies in becom-
ing a mobility supplier, offering mobility as an on-
demand service. Besides the production of the cars,
their prior business activity will shift towards data
management and analysis to provide unconditional
and convenient mobility.
Car manufacturers who act as mobility suppliers
must face new competitors. Since there is no steer-
ing wheel and no driver inside the car, there is no
longer a difference between self-driving taxis and
self-driving car sharing. Companies aim for high
occupancy rides and as few empty trips as possible.
As an add-on to the general self-driving-technology,
the cars are smart in terms of relocating, parking,
and optimizing routes based on a customer-
relationship database. Although the customers do not
own these cars, the cars must satisfy the consistent
user needs of being available whenever a user wants
to take one and having no recognizable difference in
disposability. Using big data from the customer-
relationship database helps the companies to predict
user demands and routes and automatically plan the
operations. The cars must also provide comfort,
privacy, and security. These requirements are rela-
tively easy to cover, under the assumption that full
security is technologically realizable and that the car
is used by one person alone or by a group of people
who know each other. Autonomous ridesharing is, of
course, also possible: customers use a car service
and share their ride with another – probably to them
strange – customer. When the database recognizes
that two customers want to take (nearly) the same
route, the system could suggest sharing the vehicle
and offer a discount. This special offer fulfills the
economic, ecological, and social needs of those
people who think “green” and are convinced sharers.
To meet the situation-dependent user demands,
car manufacturers and the mobility suppliers can
organize their fleets. They can provide vehicles
equipped as offices, vans, convertibles, and small
city cars with a different number of seats. Fleets
must be large enough to guarantee availability and
reliability. Additionally, they can offer different
service models such as pay-per-use prices or flat
rates.
Another important point of the autonomous mo-
bility services scenario is the trend towards inter-
modal services that are almost hidden for the cus-
tomers. Customers chose a route from one destina-
tion to another and pay for one ticket per travel.
With intermodal services, the transition between the
different mobility modes is almost seamless, such as
taking the train for a long distance journey and then
Using, Sharing, and Owning Smart Cars - A Future Scenario Analysis Taking General Socio-Technical Trends into Account
27
using a car for the last mile, all with the one ticket.
These intermodal mobility services can be offered
by individual companies, by holding organizations,
or through cooperations between different mobility
organizations. The trend towards mobility as a ser-
vice can lead to an expansion of business models
within existing companies. For example, short-range
public transportation companies could widen their
range of mobility services into different mobility
modes and therefore offer intermodal or multimodal
mobility services.
On the societal level, this scenario brings nu-
merous changes – challenges as well as opportuni-
ties. First, traditional car manufacturers are affected
as smart mobility services enable a dramatic reduc-
tion in vehicles (Spieser et al. 2014). Second, exist-
ing mobility providers, including taxis and other
driving services, are threatened by innovative mobil-
ity services as they lead to a reduction in driving
staff. Jobs will be lost since fully automated vehicles
no longer need a driver. These challenges can al-
ready be seen in the discussion about permitting
UBER (Geradin 2015). Even though other forms of
employment will arise through the new business
models, the redundancy of taxi drivers is unavoida-
ble. Furthermore, automated cars on demand will
raise the level of equality in the mobility sector.
Disabled people, older people, and other individuals
who are not able to drive independently will be more
mobile (Payre et al. 2014). Additionally, personal
parking spaces can be saved and open possibilities
for new concepts in using urban areas. In this sce-
nario, platooning is easy to implement since people
do not insist on their own speed. This leads to addi-
tional savings in fuel and infrastructure and overall
to an improved utilization of the car and the roads.
So sustainability is expected to rise in terms of eco-
nomic and ecological sustainability. At the same
time, rebound effects can occur. If using the self-
driving-service is easily affordable, reliable, and
comfortable and people can even do other things
during their ride, the total amount of rides could
increase significantly (Litman 2014). Negative eco-
logical and economic effects could arise when empty
runnings prevail as a result of relocating and opti-
mizing routes and parking. It is also possible that
consumers will mainly use autonomous car services
instead of sustainable mobility modes such as bicy-
cles or public transport.
6.3 Co-existence of Private Cars and
Services
The scenarios surely draft very extreme pictures of
the future following strictly one development path –
either ownership or usership. We are convinced that
there will be a mixture of self-driving private cars
and self-driving services. The likelihoods we defined
for the different scenarios could also be interpreted
as market segments. In the long run, mall different
variants will appear. This mixture will cause even
greater challenges since all variants must be coordi-
nated. Independent of the challenges, we assume that
there are also positive outcomes of the mixture of
autonomous private cars and mobility services. Each
scenario has advantages for specific cases.
The co-existence of private cars and mobility ser-
vices reduces both the number of cars within urban
areas and the traffic density. This improved traffic
situation will lead to private cars still being used for
business. Especially in the beginning of autonomous
mobility services, it is important to offer the custom-
er both scenarios. The incremental integration of
mobility services means that the customers can gath-
er experiences, which, in turn, could raise the ac-
ceptance of the mobility services. But still it is im-
portant that the customers have a choice of mobility
modes. A roll-out concept for autonomous mobility
services could be incrementally integrating these
services within the taxi or short-range transit sector.
7 CONCLUSIONS
Smart and self-driving cars seem to be the next ma-
jor leap the automotive industry is trying to achieve.
Digitalization challenges the automotive industry to
rethink or even change their business models to meet
the customer’s demands. With regard to this, other
studies outline digitalization’s challenges (e.g., tech-
nological, ethical, and legal) and effects (e.g., on
mobility practices, safety, sustainability, and service
markets). Our analysis confirms to a large extent the
findings of earlier scenario analyses concerning
assumed trends, pre-conditions, and possible future
scenarios. In this paper, we have demonstrated that
future car scenarios should not be studied in isola-
tion but should consider general socio-technical
megatrends associated with digital connected sys-
tems and innovative usership models. This general
view then gives an orientation, informs decision
makers, and enables them to re-evaluate the status
quo of the trends by continuously checking the criti-
cal assumptions. For the digitalization trend to pro-
ceed, it is crucial that the digital connection of goods
is ubiquitous, which basically depends on society’s
readiness. For a usership-orientated society to pre-
vail over an ownership-oriented society, consumer
ICE-B 2016 - International Conference on e-Business
28
attitude must shift. Depending on whether the criti-
cal conditions are realized or not, different scenarios
occur, with two of them being most likely and suited
to meet the needs of individualized lifestyles and the
demands of sustainable societies.
With regard to the business development, we
have outlined that owner- and usership-oriented
smart car scenarios are most likely and can realisti-
cally co-exist in the medium to long term. Both
constitute different markets with specific character-
istics that business models have to consider. For the
private market, our analysis shows that smart cars
should not just satisfy pragmatic mobility needs but
must also address hedonic and symbolic values such
as freedom, driving fun, or providing a status sym-
bol. Here the automotive industry is running along
an evolutionary development path characterized by
mainly technological advancements. For the service
market, our analysis shows that hedonic qualities are
less important. Instead the competitive position is
based on the guarantee of a high service level with
regard to availability, flexibility, comfort, usability,
and attractive pricing. This combination leads to a
revolutionary development with a major impact on
traditional business models. But it is questionable if
car manufacturers acknowledge theses disruptive
changes. Experience shows that traditional technol-
ogy companies tend to stick to their top seller and
react too late (Lucas and Goh 2009).
Concerning scope and limitation, it has to be
mentioned that the future scenario analysis is inher-
ently characterized by uncertainty. Unanticipated
disruptive phenomena cannot be forecasted. A max-
imum objectivity was aimed at, but a bias cannot be
entirely excluded as conditions and probabilities
have been evaluated intersubjectively by the authors.
Also the results of this study are only representative
for Western societies. Future research should vali-
date the findings by using supplementing methods
such as expert interviews, consumer surveys, appro-
priation studies or different experimental design to
identify acceptance and key success factors of inno-
vative business models for the different mobility
scenarios.
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