Business models and tariff simulation in car-sharing services

Abstract

The paper considers an important new and growing business in sustainable transportation, car-sharing services. This is, to our knowledge, the first comprehensive analysis of car-sharing services from the business model point of view. Specifically, we apply and introduce a standard and reproducible way to compare the business models of car-sharing companies. Our analysis results show that a crucial issue in defining car-sharing services is the creation of customized tariff plans. Thus, as a second contribution of our paper, we introduce a specific solution based on Monte Carlo simulation. This tool simulates the existing price and tariff policies or the introduction of new ones for different profiles of car-sharing users, according to different mobility needs and the traffic congestion of the urban area. As an example, we use our methodology to provide an in-depth description of the situation in the city of Turin, Italy.

Full text

Business models and tariff simulation in car-sharing services
Guido Perbolid,a, Francesco Ferreroc, Stefano Mussod, Andrea Vescob
aCIRRELT, Montreal, Canada
bIstituto Superiore Mario Boella, Turin, Italy
cLuxembourg Institute of Science and Technology, Luxemburg
dICT for City Logistics and Enterprises - Politecnico di Torino, Turin, Italy
Abstract
The paper considers an important new and growing business in sustainable transportation,
car-sharing services. This is, to our knowledge, the first comprehensive analysis of car-sharing
services from the business model point of view. Specifically, we apply and introduce a standard
and reproducible way to compare the business models of car-sharing companies. Our analysis
results show that a crucial issue in defining car-sharing services is the creation of customized
tariff plans. Thus, as a second contribution of our paper, we introduce a specific solution based
on Monte Carlo simulation. This tool simulates the existing price and tariff policies or the
introduction of new ones for different profiles of car-sharing users, according to different mobility
needs and the traffic congestion of the urban area. As an example, we use our methodology to
provide an in-depth description of the situation in the city of Turin, Italy.
Keywords: Car-sharing, Business models, GUEST, Lean Business, Tariff simulation.
1. Introduction
According to the Intergovernmental Panel on Climate Change(IPCC), the transport sector
was responsible for 11% of the increase in total annual anthropogenic greenhouse gas (GHG)
emissions between 2000 and 2010, estimated in 10Gt of carbon-dioxide equivalents, with 14% of
world GHG emissions released by the transport business. Considering only urban areas, approx-
imately 80% of global GHG emissions originate in cities, with a significant share corresponding
to transport activities (Firnkorn and M¨uller,2015a;World Bank,2013). The prevalence of pri-
vate vehicle utilization for mobility purposes in cities with low-density development configures a
largely irreversible pattern, which must be avoided in future urbanization and reversed in many
existing cities that suffer from the consequences of this development model. In 2014, there were
1 billion passenger cars worldwide, and this number is projected to increase to 2.8 billion by
2050 (although this figure might be mitigated by city management policies). The consequences
of the predominant use of individual vehicles in car-centric cities are well known: congestion,
noise, higher energy use, parking shortage, inefficient land use, pollution, waste, and climate
changes (Firnkorn and M¨uller,2015a;Perboli et al.,2014).
Among the alternatives, car-sharing is an innovative mobility option that arises as one of the
solutions for mobility improvement and reduction in private car utilization. Car-sharing systems
are becoming increasingly popular all over the world, and the number of available shared vehicles
Preprint submitted to September 18, 2017

has also increased because new vehicles have been added to the fleets of existing operators
and new operators have begun their activities. Car manufacturers (such as Daimler, BMW,
and FCA group) are directly involved in car-sharing operations, searching for new channels
to market their cars. As car-sharing emerges as a mainstream alternative for mobility, the
competition among different players is increasing, as is the motivation for the pursuit of further
development of services and sources of differentiation between new competitors. Despite the
emerging importance of this type of mobility and large number of papers published in the past
two decades, there is a lack of studies on the car-sharing services that link the business models
of the companies operating the service, their business development, and operational models
(Ferrero et al.,2017).
The aim of our research is to fill this gap, providing the first analysis of the business models
of car-sharing companies, applying it to a set of companies operating in the same catchment
area, and comparing them. Thus, the first contribution of this paper is to provide a solid
and reproducible methodology to compare the behavior of car-sharing companies, starting from
the value proposition and business model up to the definition and validation of the tariffs to
use, in order to increase market penetration. Four different car-sharing companies are selected
for this analysis: Car2Go (Car2go,2015;Firnkorn and M¨uller,2011), Enjoy (Enjoy,2015), Car
City Club (IoGuido) (IoGuido,2015), and BlueTorino (BlueTorino,2016). These companies are
chosen to cope with a large set of possible actors, including two large-sized companies sharing the
same catchment area (Car2Go and Enjoy), a traditional station-based company (IoGuido), and
a large company using a fleet of green vehicles (BlueTorino). Moreover, all of these companies
have a part of their catchment area in common: the Turin urban area. A comparative analysis
of the companies is conducted, highlighting the main aspects of the companies’ business models
and the different solutions used to create value and competitive advantages through service
differentiation.
The second contribution to the literature is related to the tariffs and customer segments that
should be of interest. In fact, car-sharing services are moving from a single tariff based on time
or distance to a more complicated mix of offers, as occurred in the Telco market about 10 years
ago. The big difference in the car-sharing market is the availability of a consolidated database on
user preferences. Thus, we develop an evaluation tool for the economics of car-sharing utilization
by introducing a Monte-Carlo-based simulator. This tool simulates the existing price and tariff
policies or the introduction of new ones for different profiles of car-sharing users, according to
different mobility needs and the traffic congestion of the urban area. Due to the presence of all
of the companies under study in the urban area of Turin and to the availability of a large set of
data related to the traffic congestion (Perboli et al.,2017b), Turin is chosen for our simulations.
The information on the different car-sharing companies is collected through the company
websites and other public documents. After the data collection phase, information on differ-
ent car-sharing providers is compared using the GUEST methodology (Perboli,2016;Perboli
and Gentile,2015), in order to find commonalities and differences between different business
strategies. The data collected in this first phase are also used to set the parameters for the
Monte-Carlo-based simulator, with the aim to calculate the costs related to car-sharing usage
for different customer profiles, and to compare them with the costs related to car ownership.
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The remainder of the paper is organized as follows. Section 2recalls the relevant literature.
Section 3introduces GUEST, the Lean Business methodology applied in the study and data
gathering. Section 4presents the selected car-sharing operators and their business models,
while a comparative analysis of the companies and their business models is presented in Section
5. The simulation environment of tariffs and user costs is presented in Section 6, while the
resulting comparison of the cost structures of the service utilization of the analyzed car-sharing
companies is discussed in Section 7. Finally, the conclusions are reported in Section 8.
2. Literature review
Despite the emerging importance of this type of mobility and the large number of papers
present in the scientific literature, to the best of our knowledge, there is just one study in
which an extensive and structured analysis has been performed, in order to classify the whole
research field and determine its main streams (Ferrero et al.,2017). In fact, partial visions
and state-of-the-art reviews of car-sharing exist, but there is a lack of global vision (Jorge and
Correia,2013;Laporte et al.,2015;Shaheen et al.,2015). Existing works can be split into
two main groups: studies considering the technical and modeling aspects (Agatz et al.,2012;
Furuhata et al.,2013;Laporte et al.,2015;Schm¨oller et al.,2015;Wagner et al.,2016) and
papers dealing with the business perspectives of car-sharing obtained through surveys (Chan and
Shaheen,2012;Shaheen and Cohen,2013;Firnkorn and M¨uller,2015b;Zoepf and Keith,2016).
Regarding the first group, in Schm¨oller et al. (2015), the booking data of a German free-floating
car-sharing system are analyzed in order to identify the factors influencing customer demand,
finding that socio-demographic data are suitable for making long-term demand predictions.
From the perspective of car-sharing providers, Wagner et al. (2016) present a method that
provides strategic and operational decision support, in order to explain the spatial variation
in car-sharing activity in the proximity of particular points of interest. Free-floating electric
car-sharing fleets are addressed in Firnkorn and M¨uller (2015b), through an online survey of
Car2Go users, with the aim to analyze the willingness to adopt these services as a substitute
for car ownership. Zoepf and Keith (2016) analyze the results of a discrete choice survey
administered to members of a North American car-sharing operator, with the aim to quantify
how users value price, distance, schedule, and vehicle type. Recently, the increasing interest
in autonomous vehicles has been addressed in Krueger et al. (2016), in order to identify the
characteristics of users that are willing to join a car-sharing service based on these types of
vehicles. The results show that service attributes, such as travel cost, travel time, and waiting
time, may be critical to determining the use and acceptance of shared autonomous vehicles.
Considering the collaboration between governments and private companies, in Terrien et al.
(2016), the authors propose a framework to foster the collaboration between the public and
private sector, with the aim of providing recommendations for both sectors. Finally, Kent
(2014) analyzes how car-sharing services can address the health problems connected to the use
of private cars, highlighting the potential health benefits related to the adoption of more active
modes of transportation.
Regarding survey-based studies, they mainly use expert opinions to determine the key factors
of the potential growth of the car-sharing market. Shaheen and Cohen (2007) collect 33 expert
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surveys on an international basis (21 countries), showing that the main key factors character-
izing car-sharing operations are related to member-to-vehicle ratios, market segments, parking
approaches, vehicle and fuel variety, insurance, and technology. Similarly, in Shaheen et al.
(2009), a 10-year retrospective in the Canadian and U.S. markets is used to analyze the car-
sharing evolution in North America through the three phases of market development: market
entry and experimentation, growth and market diversification, and commercial mainstreaming.
Based on a survey of 26 existing organizations in North America, Shaheen et al. (2006) shows
that the growth potential of car-sharing membership is between 6.9% in Canada and 12.5%
in the U.S. The same study identifies car-sharing education, impact evaluation, and support-
ing policy approaches as the key factors for car-sharing growth. Unfortunately, the findings of
these surveys are quite limited due to the methodology in use (expert surveys only), and they
disregard the underlying business model. Finally, Shaheen and Cohen (2013) provides a large
depiction of car-sharing services, again, using a survey of over 26 experts, showing the directions
of market growth, but they lack a clear description and comparison of the business models.
To our knowledge, the work of Beutel et al. (2014) is the main study considering the busi-
ness of sharing mobility services. In detail, the authors mainly focus on car-pooling, using a
framework linking business factors and service strategies. The framework considers the service
aspects, partially considering additional issues, as the business model, its link to business de-
velopment, and the value proposition of the different car-sharing companies. More recently,
different pricing schemes are analyzed in Ciari et al. (2015) in order to define how different pric-
ing strategies can lead to differing service demand. Geographic, financial, and environmental
factors are examined by Rabbitt and Ghosh (2013) using multiple alternative scenarios applied
to the collected travel information of the Irish population in order to evaluate the market po-
tential of car-sharing. The results show how car-sharing systems could lead to cost savings for
members, a reduction in travel-related pollution, and increase in the share of sustainable modes
of travel.
While such a perspective, which lacks a focus on the business model, might be partially
tolerated in the pioneering phase, it must be compulsorily considered in a more mature phase
of the market (Osterwalder and Pigneur,2010). Moreover, there is a lack of studies that focus
on the economic implications of car-sharing membership in the daily routine of members.
Thus, this issue is addressed in this paper. First, a full and detailed study of the value propo-
sitions and business models of four car-sharing companies competing in the same catchment area
is presented. Second, an analysis of the cost benefits related to car-sharing membership for dif-
ferent customer profiles, compared with the costs related to car ownership, is performed. In
particular, the analysis of two different car-sharing modes (traditional and free-floating) shows
that the free-floating mode, in conjunction with an aggressive and well-studied tariff scheme,
can also effectively push the usage of green vehicles, particularly electric vehicles. Although
there are already extensive studies concerning the potential impacts of car-sharing, user be-
havior, and potential demand, as well as case studies of operating companies, few have been
conducted using a comparison of different car-sharing companies. More specifically, there is a
lack of analysis on the coexistence of different car-sharing companies in the same environment,
and how they can operate in a competing scenario (a situation that becomes more common
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given the car-sharing market growth and entrance of new players in the market).
3. Methodology and theoretical basis
The definition of the methodology is crucial. On the one hand, the relative novelty of car-
sharing services pushes the consideration of the methods developed in the literature for startups
(Osterwalder and Pigneur,2010;Ries,2011). On the other hand, the methodology should be
adaptable to existing companies and, thus, repeatable. For these reasons, we adopt the GUEST
methodology, developed in recent years by Perboli and Gentile (Perboli,2016;Perboli and Gen-
tile,2015), which is a Lean Business methodology extending the work done by Osterwalder
(Osterwalder and Pigneur,2010) as well as the Lean Startup movement, adapting their results
to the environment of existing companies and to products or services of companies that are part
of a Multi-Actor Complex System (MACS). The GUEST methodology is originally a strate-
gic methodology for supporting the actors in a Multi-Actor Complex System in making their
decisions during the development of new products and services. One of the main aspects of
this methodology is the standardization of the heterogeneous tools usually used for business
development. In this paper, the standardization capabilities of the GUEST methodology are
exploited with the aim of comparing the strategies of the different car-sharing operators exam-
ined. GUEST is the acronym of the five consecutive steps of the methodology itself, which have
the following meanings:
Go: a full description of the company profile, its present behavior and business develop-
ment status, its environment, the external actors in the system, and their interactions is
established;
Uniform: the knowledge of the system must be assessed in a standard way, in order to
obtain a shared vision of the MACS. In particular, in this phase, the governance and
business models are explicitly described by means of the Business Model Canvas (BMC)
(Osterwalder and Pigneur,2010);
Evaluate: the governance and business models are assessed in a series of actions. The full
structure of the costs and revenues is explicitly described in order to evaluate the goals of
the initiative. Moreover, a series of problems and opportunities is identified, as well as the
actions that can manage them and the KPIs to measure the effectiveness of such actions;
Solve: given the specific problems and actions highlighted to cope with them, a list of
operational models is proposed;
Test: the actions are actually implemented in case studies and their performance is eval-
uated. Moreover, the findings of the actions are disseminated according to the Results
Dissemination Plan.
Regarding the present application of the GUEST methodology to car-sharing services, the
five steps are as follows:
Go: the data of the car-sharing companies are gathered by means of primary data;
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Uniform (Section 4): for each company, a Business Model Canvas (BMC) is derived;
Evaluate (Section 5): a deep analysis and comparison of the BMCs is performed, finding
tariff evaluation as the main key linking factor between the business and operational
models of car-sharing companies. Therefore, it is a priority to have a tool that is able to
evaluate the impact of tariffs on different types of customers;
Solve (Section 6): a Monte Carlo method is developed to obtain, for a given customer
type, the real cost paid by users under real congestion rates in urban areas;
Test (Section 7): the Monte Carlo method is then tested on three typical customer types
(commuters, professional users, and casual users) in the urban area of a medium-sized
city, Turin.
The primary data needed for the first step (Go) consist of information on the companies in-
cluded in the analysis, regarding their strategies and business aspects. The main sources are the
financial statements and other public data made available by companies listed in stock markets,
company websites, and official data provided by the companies themselves. Other sources are
scientific publications focused on the companies included in this study (when available), public
contracts in the case of publicly owned companies, and regulation contracts for the operation
of private companies.
4. Business Model Canvas
The aim of analyzing the company’s business models is to identify the resulting differences
and similarities between different service modes, including roundtrip car-sharing, point-to-point
station-based car-sharing, and free-floating car-sharing. The pool of companies includes differ-
ent private-sector and public operators in order to understand the eventual differences in the
business models of both sectors. Furthermore, another objective is to understand the implica-
tions of electric vehicles in the business model; in fact, a company operating only with electric
vehicles (BlueTorino) is included in the comparison.
A description of the selected car-sharing companies is established based on the identification
of their main business aspects, which are represented by the utilization of the Business Model
Canvas. This is a strategic management and entrepreneurial tool (Osterwalder and Pigneur,
2010) that visually illustrates the business model of a company or organization, which describes
the rationale of how an organization creates, delivers, and captures its value according to Oster-
walder. Given its user-friendly display of information in a graphical template, it allows an easier
understanding of a company, the creation of alternative scenarios, and evaluation of possible
tradeoffs between the elements that compose the system.
For these reasons, the construction of the BMC for each company studied is considered
a pertinent methodology to endorse a comparative analysis. The key factor determining the
success of the canvas can be identified by the immediate display of the main information needed
to determine the areas in which the managerial team should concentrate its efforts. Moreover,
the relationships between the elements of the organization and the way they should be logically
linked are presented in an efficient way.
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The BMC consists of nine different building blocks, which are defined as follows.
Customer segments: these are defined as the different segments (of people and/or organi-
zations) that a company aims to reach and serve.
Value proposition: this is the combination of products and services offered by the company
to satisfy the needs of its customer segments. Basically, it determines why customers
choose one operator according to the value the company creates for clients with the service
and product mix delivered.
Channels: these are how a company reaches and communicates with its customer segments
to deliver a value proposition. The communication, distribution, and sales channels com-
prise the company interface, with its clients playing a very important role in the customer
experience.
Customer relationships: these are the types of relationships a company establishes with
specific customer segments, enabling client acquisition and retention as well as business
development.
Key resources: these are the assets needed to guarantee the company operations, customer
relationships, creation and offering of a value proposition, and revenue.
Revenue streams: these are the sources of the revenue that the company generates from
the commercialization of its products and services to each of its customer segments.
Key activities: these are the most important actions that a company must take on a regular
basis in order to offer a value proposition, reach markets, maintain customer relationships,
and earn revenue.
Key partnerships: these are the networks of partners and suppliers necessary to make
the business model operate correctly. Through the creation of partnerships, companies
can optimize the allocation of resources and achieve economies of scale, reduce risk and
uncertainty in the competitive environment, acquire particular resources and activities,
compete in broader markets, promote their brands, and reach new clients.
Cost structure: the main costs incurred to operate a business model are detailed, including
the cost for the acquisition of key resources, partnerships, and activities.
4.1. Car2Go
Car2Go, a subsidiary of Daimler AG, was founded in 2008 in the city of Ulm, Germany, and
currently offers car-sharing services across 30 cities in eight different countries in Europe and
North America, serving over one million customers with about 13000 vehicles (Car2go,2015).
The company is the first to operate a free-floating car-sharing service, and is one of the biggest
players in the car-sharing market worldwide (Firnkorn and M¨uller,2011). The business model
is the same in every location in which the company operates, offering free-floating rentals, and
is summarized in the BMC in Figure 1.
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A key element of Car2Go strategy is operating on a large scale in cities, covering the most
important central areas with a high number of vehicles in its fleet. As a result, the company
aims to meet customer demand with its high availability of vehicles, generating greater revenue
and guaranteeing higher customer satisfaction. The characteristics of the vehicle fleet also play
a key role in brand recognition; the fleet is completely composed of Smart ForTwo vehicles,
gasoline- or electric-powered (recently introduced in some selected cities), produced by Smart
Automobile, a division of Daimler AG. All of the vehicles are painted in white and blue with
the company name, logo, and slogan to create a strong visual identity, allowing the vehicle to
serve as a marketing channel, increasing brand recognition.
Subscription fees (charged upon the registration of new customers) and rental fees (including
rental, fuel consumption, mileage, insurance, parking in authorized areas, and maintenance) are
the two main revenue streams for the company.
Customers can locate and reserve a vehicle through the Car2Go website, by means of a
smartphone application, or directly on the street where the car is parked; the website and
application also serve as marketing and communication channels. Car2Go has mainly focused
its marketing efforts on the segment of young adults, which corresponds to a relevant percentage
of users, and corporate clients. Its value proposition is based on delivering an innovative and
environmentally friendly transportation service, offering flexible urban mobility. The service
has been designed to complement the available transportation alternatives, meeting customer
demands that are not satisfied with public transportation services or with the use of private
vehicles; the value proposition is disclosed through the website and mobile application. Other
channels to reach the population and conquer new clients are marketing campaigns launched
in areas with a high circulation of people in cities, especially when the company is starting its
operations in a new location. Customer relationships are automated, and the customer interface
consists of the website and application, which are developed to provide all of the necessary means
for customers to help themselves on a self-service basis.
In order to leverage its operations, the company works in partnership with local governments,
whom it can collaborate with to obtain public spaces for designated parking areas or establish
agreements for the use of standard parking spots by company customers as well as for free
circulation in limited traffic areas. A key partnership has been established with Europcar, an
international car rental company, with the aim of having insights from the extensive knowledge
of the car rental company, in the areas of fleet management and logistics, and from cross-selling
and cross-marketing practices. In order to reduce personnel costs and maintain the condition of
the cars in usage, the company also establishes a partnership with its own clients, stimulating
them to refuel the vehicles in exchange for free service minutes.
4.2. Enjoy
Enjoy, a car-sharing company created by ENI, an Italian oil and gas company, started
operating in Milan in the end of 2013 with great success, becoming in a few years the first
Italian operator in terms of number of users with the 57% of the Italian Market Share (Sharing
Mobility Observatory,2016). Besides Milan, it is already present in Rome and Florence and,
in the first half of 2015, launched its services in Turin. The Enjoy business model is based on
free-floating car rentals; customers can register themselves for free on the company website, and
8

the service becomes immediately available (Enjoy,2015). The business model is the same in
every location in which the company operates, offering free-floating rentals, and is summarized
in the Business Model Canvas in Figure 2.
The main customer segments that Enjoy serves are, similar to the other car-sharing compa-
nies, private users and corporate clients. Enjoy charges a fee per minute of utilization, which
already includes the costs of fuel, parking, maintenance, and insurance, but hourly and daily
discounted fees are also available. In agreement with local authorities, Enjoy vehicles are al-
lowed to circulate in limited traffic zones in the city centers, and can be parked in regular, paid
public parking spots; the municipalities, on the other hand, usually fix a maximum limit for the
number of vehicles operating in a fleet and charge an annual fee per active vehicle.
Together with ENI, Enjoy’s main partners are Trenitalia, the main Italian train operator
company (the companies have agreements for the integration of services and mutual collabora-
tion); Fiat Chrysler Automobiles (FCA), an Italian car manufacturer (supplier of the Fiat 500
fleet, painted in red and carrying the company logo on the doors); and CartaSi, a credit card
company with which Enjoy has specific agreements for the payment system and services. The
partnership with Trenitalia is strategic for Enjoy in its focus on corporate clients, which rep-
resent an important customer segment. Both companies benefit from cross-marketing, as each
company announces the partner services in their customer channels. The company has also
established partnerships with other supplier companies, for example, a company specializing in
vehicle cleaning and uniform supplier for the service team. Other important partnerships must
be negotiated with the local municipalities for the regulation of the service as well as for the
guarantee of circulation and parking permits for service users in standard public parking spots
inside the area covered by the service.
Similar to other car-sharing companies, other value propositions are the accessibility, flexi-
bility, practicality, and environmentally friendly characteristics of the service.
Customer relationships are automated, and the customer interface consists mainly of the
website and mobile application, which are developed to provide all of the necessary means for
customers to help themselves on a self-service basis; a 24-hour-operating call center is also
available for customer assistance. Enjoy does not charge registration or fixed annual fees to its
clients. Therefore, rental fees are the main revenue stream; the company charges an all-inclusive
per minute fee.
Enjoy also incurs the payment of annual fees to municipalities in order to be allowed to
operate and benefit from specific terms agreed upon by local municipalities, for example the
possibility of parking the cars in any standard paid parking spot and circulating in limited
traffic zones.
4.3. Car City Club (IoGuido)
Car City Club (IoGuido) is a car-sharing company run by the city municipalities; it is an as-
sociate member of the car-sharing initiative (ICS), a national coordination structure promoted
and sustained by the Italian Ministry of the Environment. Founded in 2002, it is the first
car-sharing company of Turin and, as a member of ICS, it has a market share of 3% (Sharing
Mobility Observatory,2016). The aim of the ICS is to offer support to local municipalities inter-
ested in developing local car-sharing services, stimulating the creation of a national car-sharing
9

network and promoting sustainable mobility policies (IoGuido,2015). The associated companies
must comply with homogeneous standards regarding services, emissions, and safety, in order
to guarantee a minimum quality, the interoperability among participant cities, and common
services and user procedures. Given the standards and knowledge supported by the ICS, the
associated companies’ business models are the same, with similar operational procedures, as
illustrated in Figure 3.
IoGuido offers two different rental possibilities: the classic modality, in which customers
must deliver the car to the same parking area at which they started the rental, and one-way
rental, in which customers can deliver the car to a parking area different to that at which they
started the rental. In both cases, customers must make a previous reservation, indicating the
vehicle that they want to rent, initial location (according to availability), renting period, and
location where they want to deliver the car at the end of the rental. The company charges a
fee per km in addition to an hourly fixed fee; prices vary according to the vehicle chosen, rental
conditions (classic or one-way), and period of the day, and the fee per km decreases with an
increase in the distance traveled. Moreover, daily rentals are also available.
IoGuido’s main customer segments are both private users and corporate clients, who com-
plement or substitute their fleet for the shared vehicles; among the clients, there are also public
entities, for example, the city municipality. The company value propositions are based on the
creation of an alternative for mobility, complementing the other existing public transportation
systems with a low environmental impact, offering its users the possibility of utilizing a private
vehicle without the necessity of owning one. Customers recognize the value in the wide variety
of vehicles in the company fleet, which allows them to choose a model according to different
needs (in recent years, the fleet has increased with the inclusion of electric vehicles).
The main channels to reach customers are the company website, a smartphone application,
and, different from other car-sharing companies, a call center, through which clients can register
themselves and make car reservations. Customer relationships are, therefore, mainly automated,
with interfaces consisting of the website and application.
IoGuido charges an annual fee to its customers, to keep their profiles active, in addition to
rental fees. Annual fees vary according to user characteristics (private or corporate clients) and
the service options. Users can choose to pay an annual fee to have full access to the service
during the year or, alternatively, they can pay a smaller fixed activation fee every time they use
the service (in addition to hourly and per km fees).
The key company resources required to make the business model work are the vehicle fleet,
exclusive parking spots, service team, and website and smartphone application. Besides the
car rental, other key activities must be performed to keep the business running properly: the
maintenance of the vehicles (including cleaning and fueling), management of the fleet (vehicle
repositioning, checking if cars were delivered in appropriate spots, etc.), and customer service.
IoGuido’s main partnership is established with ICS (for technical, legal, and financial sup-
port), in association with the Italian Ministry of the Environment. Being a public service
company run by the city municipality, the company benefits from distinct advantages, namely
the gratuity for customers to park in the streets while the service is active, designated park-
ing spots in public areas, and right for its cars to circulate in restricted traffic areas, as well
10

as tax-related benefits. The company also seeks to establish further partnerships with other
companies (e.g., retail stores, shopping malls, and universities), thus offering exclusive parking
spots in these parking areas and/or other combined agreements and promotions, in order to
reach new clients. IoGuido has also established other partnerships or agreements with strategic
suppliers, for example, car manufacturers (the vehicle fleet is composed exclusively by FCA
Group cars), fuel distributors, and insurance companies.
Some of the costs are subsidized by the Italian Ministry of the Environment, in the scope of
stimulating local municipalities to develop car-sharing companies, in association with the ICS
organization, in order to improve urban mobility with integrated, more effective, and environ-
mentally friendly services.
4.4. BlueTorino
BlueTorino is a car-sharing service run by the Bollor´e Group, an International company
operating in different fields, including transportation and logistics. Among others, Bollor´e
Group manages Autolib, an electric car-sharing company operated in association with Paris
Municipality. With more than 2500 vehicles and 875 parking stations, with over 4000 charging
points, Autolib is the first extensive, public electric car-sharing system ever created (BlueTorino,
2016). In the end of 2013, Autolib expanded its operations in France, offering its services in
Lyon, and at the beginning of 2014, it started operating in Bordeaux. Bollor´e group has also
signed deals to start operating experimental offshoots of Autolib in Indianapolis (U.S.) and
London (U.K.) in 2015. BlueTorino’s business model is reported in Figure 4.
The company started its operations in Turin in 2016, being the first fully electric car-sharing
service operating in the city. Although the development of the service is still not complete, the
company foresees having, at the end of the first phase, 150 vehicles, 80 charging stations, and
250 parking lots.
The service aims to meet the demand of different segments of customers, comprising fre-
quent users, occasional users, and tourists, offering different service plans in order to reach
customers with different needs and characteristics. BlueTorino’s service is based on full electric
powered Bluecars, a model developed by Bollor´e Group in association with Pininfarina, the
independent Italian car designer firm and coachbuilder, and produced by CECOMP, an Italian
car manufacturing company. The main channels accessed by customers are the website and
smartphone application; through these channels, customers can obtain all of the information
concerning the company (services, fares, etc.); find the closest station; check for available cars,
parking, or charging slots; and make reservations. The website and mobile application are also
the main customer interfaces for the company. Fixed and per minute fees are the main revenue
streams for BlueTorino, whose customer segments are mainly private clients, with special fees
for younger ones (from 18 to 25 years old). Furthermore, it is possible to choose a single day
subscription (mainly for tourists).
The essential resources for BlueTorino are the vehicle fleet and stations with parking spots
and charging facilities; in addition, the company relies on its website and smartphone application
as the main customer interfaces, which are fundamental to properly delivering the service. In
order to manage operations, another key resource is an integrated information system, contain-
ing all of the necessary information regarding revenue streams, customer profiles, reservations,
11

car availability, and positioning, which are fundamental inputs for the correct operation of the
service by the management team.
The key activities for BlueTorino are the maintenance of vehicles, management of the fleet,
and recharging of vehicles. However, the company still has to manage the fleet and eventu-
ally reposition vehicles that might be overly concentrated in some areas of the city. Another
important activity is customer service; the service team must assist the users in any case of
need and be available 24 hours/day. The development and maintenance of information systems
is also quite important for the managerial activities in the company. Besides, the develop-
ment and maintenance of the website and smartphone application are fundamental for service
performance, as these two platforms are the main customer interfaces.
The main partners of BlueTorino are, besides Bollor´e Group, Bluecar, responsible for the
development and commercialization of the electric vehicles, Pininfarina, coachbuilder and car
designer company, batScap, a research center dedicated to the development of the batteries,
and CECOMP, the vehicle producer.
5. Comparative analysis of car-sharing companies
The objectives of the comparative analysis are to identify the advantages and limitations
of the different strategies adopted by the companies and to analyze the conditions in which
the companies might coexist and compete in their shared markets. We summarize the main
characteristics of the different car-sharing companies in Table 1. All the data come from the
latest report of the Italian Sharing Mobility Observatory (Sharing Mobility Observatory,2016)
and refer to year 2015. The data of BlueTorino market share and number of vehicles are
not presented because still not consolidated (the next report will be available in November
2017). To begin with, all the companies share value propositions inherent to the car-sharing
concept, offering an alternative for mobility with low environmental impact, complementary
to the available public and private modes of transportation and economically efficient when
compared to car ownership. However, the degree to which the companies succeed in delivering
these values to their customers depends on their operational characteristics.
One of the main sources of differentiation for car-sharing operators is the service model
adopted, which is also evaluated in the value proposition of the companies. The option for
traditional roundtrip car-sharing reduces the complexity of fleet management, since the vehi-
cles are returned to the same dedicated parking spaces where they were initially rented, but
provides less flexibility for users. Consequently, this operation model, which is one of the two
adopted by IoGuido, is not the most convenient for the customers’ routine needs of trans-
portation between their homes and workplaces, being more suitable for occasional usage. The
point-to-point station-based service model, on the other hand, grants customers more flexibility
when compared to round-trip car-sharing. As a tradeoff, the car-sharing operators face more
challenging logistics operations, since the positioning of the cars is subject to imbalances result-
ing from concentrated demands and usage patterns. Thus, it is a key issue for the operators
to effectively deal with this problem in order to increase vehicle usage and market penetration.
The point-to-point free-floating service model, offered by Enjoy and Car2Go, is a car-sharing
service that provides customers with the maximum flexibility among the existing operational
12

Car2Go Enjoy Car City Club (ICS) BlueTorino
Service start
(year)
2015 2015 2002 2016
Number of
vehicles 1880 (Italy) 2080 (Italy) 594 (Italy) NA
Type of vehicles Fuel Fuel Fuel + Electric Electric
Market share 32.3% (Italy) 57.4% (Italy) 3% (Italy) NA
Service type Free floating Free floating Station based Station based
Pricing strategy Subscription fee (€29 for the first
year) + Variable fee (€0.29/min.) Variable fee (€0.25/min.) Fixed fee (€59/year) + Variable fee
(€3.68/hour + €1.08/km for distances
higher than 100 km)
Fixed fee (€60/year) + Variable fee
(€0.18/min.)
Partnerships
Europcar
Local governments
Customers (refuelling agreement)
Insurance companies
Fuel distribution companies
ENI
Trenitalia (Italian rail operator)
FCA (vehicle supplier)
CartaSi (credit card company)
Other commercial companies and
suppliers
Local municipalities
Insurance companies
Municipality
Car Sharing Initiative (ICS)
FCA (vehicle supplier)
Insurance companies
Retail companies, universities and
other promotion partners
Municipality
Bollorè Group
Bluecar
Pininfarina (car designer)
CECOMP (car manifacturer)
batScap (research center dedicated to the
development of the batteries)
Table 1: Characteristics of the different car-sharing companies and their market shares (Sharing Mobility Ob-
servatory, 2016). The detailed data of BlueTorino are not reported because they will be available in November
2017.
13

models. Besides reducing the need for dedicated parking spaces, this model carries the highest
fleet-management complexity. Moreover, the elimination of proprietary parking spaces might
create difficulties for customers in areas where it is hard to find available standard parking
spots. This problem is usually addressed by the free-floating car-sharing companies with the
creation of designated parking spots in critical areas, such as train and metro stations. For
the point-to-point free-floating service model, fleet availability is extremely important and must
be delivered by the car-sharing companies if they wish to reach the aforementioned objectives,
especially if they aim to substitute car ownership.
Enjoy, Car2Go, and BlueTorino rely on large-scale operations with large fleets to address this
issue, trying to minimize fleet-management efforts and allowing for the spontaneous use of the
service by their customers to relocate the largest percentage of vehicles. The characteristics of
the vehicles offered in the fleet are also of considerable value to customers; usually, car-sharing
companies focus on compact urban vehicles, which are easy to drive and can be parked in
limited-space areas. The standardization of fleets provides companies a stronger visual identity,
increasing brand recognition by customers, and it also facilitates fleet acquisition and partnering
with vehicle suppliers, in addition to reducing maintenance costs. IoGuido, on the other hand,
offers a choice of different vehicle types, ranging from compact cars to sport utility vehicles
and cargo vans, meeting different customer needs. BlueTorino has opted for a purely electric
vehicle fleet, which is imperative for their strategic objective. This option is motivated by
environmental concern and the belief of further value creation for educated customers, who
are aware of the environmental impact caused by the extensive use of fossil fuels. However,
electric vehicle fleets increase companies’ operational complexity, since such vehicles have lower
range and demand considerably more time for recharging and the need for proprietary charging
stations.
Building a large customer base and increasing the average service usage among customers
is very important for car-sharing companies. Private companies must reach a minimum target
of service hours to breakeven and turn such operations into a sustainable business, while public
companies must meet the public demand to create the aimed positive impacts on traffic, mobility,
and the environment. The car-sharing companies focus on three aspects to reach their customer
bases, corresponding to three of the BMC building blocks: customer channels and marketing
efforts, partnerships to target specific customer segments, and definition of service plans and
billing strategies (which compose the revenue streams) to meet customer demands. To begin
with, all of the considered companies rely on common customer channels, reaching their clients
through the advertising of their services on proprietary websites or by word of mouth, and
supporting their client base through smartphone applications, call center services for personal
assistance, and, once again, through their websites, as well as the social networking channels.
In addition, all of the companies applied similar marketing strategies for the advertising of their
services, realizing marketing campaigns in areas of high circulation in the cities in which they
operate, mainly during the launch of the services.
The definition of pricing strategies is also important when addressing different customer
segments, given the fact that different price structures and models of service are more suitable for
different customer needs. Among the free-floating operators, only BlueTorino provides different
14

fees for different customer targets. In particular, the company offers a one-day tariff, without a
subscription fee and with a higher per-minute fee, and a tariff for younger customers (from 18
to 25 years old), with a lower subscription fee (1 eper month) and lower per-minute fee (0.14
eper minute), while the normal tariff charges 5 eper month and 0.19 eper minute. This
could be a winning strategy, as real growth rates could exceed the projections with an increased
focus on younger individuals, who have more difficulty affording insurance costs (Shaheen and
Cohen,2007;Shaheen et al.,2006). All of the companies charge the service usage proportionally
to the rental period, and the fees already include the costs related to refueling or recharging,
maintenance, insurance, and parking.
The four companies have established buyer-supplier partnerships in order to assure a reliable
supply of the main assets necessary for their operations. Particularly, the companies Enjoy,
IoGuido, and BlueTorino have agreements with vehicle suppliers for the acquisition of their
fleets, which represent significant fixed costs. Car2Go, on the other hand, is a subsidiary of the
Daimler AG group, which produces the Smart ForTwo models used in the fleet.
Other important partnerships concern the technology necessary for the operation of the
business, including the development of integrated information systems for fleet management,
which must be connected to the devices installed in the vehicles; registration of users; billing
process; and other internal activities. Car2Go established a partnership with Europcar, a
traditional car rental company that provides the necessary knowledge for fleet management.
IoGuido, on the other hand, has the support of ICS (Car-Sharing Initiative), which supplies
the associated public companies the information systems and technology needed for operations
management.
Finally, it is vital for car-sharing companies to establish partnerships with the local govern-
ments of the cities in which they operate in order to align the services with local regulations
and establish agreements granting the companies operational conditions, regarding the use of
public spaces and parking, taxation, and other benefits. In Shaheen and Cohen (2007), parking
facilities are seen as a form of non-monetary support to operators, while in Shaheen et al. (2006),
supporting policy approaches are identified as a key factor for membership growth potential.
These agreements are, as expected, more easily handled by publicly operated companies (i.e.,
IoGuido) whose strategies and operations are aligned with those of the public stakeholders.
Privately operated companies, on the other hand, besides depending on proper regulation for
their operations, also need to negotiate the use of standard public parking spots (especially
in the case of free-floating companies), right to use public spaces for the construction of fixed
stations (in the case of station-based operations and charging stations), and other benefits (e.g.,
access to limited traffic areas) with the public authorities.
Regarding the key activities, structural similarities are identified among the analyzed com-
panies. In all cases, the core activity is the offering of short-term car rentals, and the backbone
activities necessary for the business operation are registration of users, management of reser-
vations, billing operations, fleet management, vehicle maintenance, and customer service. The
key resources are commonly comprised of the vehicle fleet; integrated information systems, de-
veloped to manage the fleet and rentals; websites and mobile applications, which are the main
customer channels; service; and management teams. Companies operating with a station-based
15

service model (IoGuido and BlueTorino) also have their proprietary parking spots, including
recharging facilities in the case of operations with electric vehicles, as important resources. The
cost structure of car-sharing companies is characterized by a high portion of fixed costs, re-
lated to fleet acquisition and the development of complex information systems to operate the
business. Station-based operators incur higher infrastructure costs for the installation of the
stations, although free-floating operators also have to install proprietary parking spots in loca-
tions with lower availability of public parking spots. Other common costs among the companies
are related to maintenance, cleaning and refueling/recharging the vehicles, fleet management
(including vehicle repositioning), municipal taxes included in the agreements for the service
authorization and use of public facilities, and personnel costs.
Thus, if we do not consider some aspects related to the different vehicle mix in the fleet,
there is not a clear characterization of the different companies. Moreover, car-sharing operators
use the quite old-style marketing strategy of creating the market by showing their products
literally on the streets. Unfortunately, even if revenues are increasing, profitability is still not
attained. For example, Car2Go, the leader of car-sharing services with about 13000 vehicles
and a presence in 30 cities between Europe and North America, presents constant negative car-
sharing revenue and a loss of about 42 million euros in 2014 (Daimler AG,2014,2015). This
limited usage of more complex marketing strategies is restricting the penetration of car-sharing
services. In particular, more attention should be given to the tariffs and their effects on the rates
for specific customer segments, such as corporate users. This is not a trivial task; in fact, in
order to assess the real impact of a specific tariff on a single customer type, we need simulation
tools able to incorporate different sources of information, including socio-demographic data,
traffic simulation, and user-behavior simulation.
6. Monte-Carlo-based simulation
In order to perform our analysis, we develop a Monte-Carlo-based simulation. The aim of
the simulator is twofold: first, to provide the managers of car-sharing companies with a tool that
can quantify and certify the cost of the car-sharing service for a given user type of a specific city,
and, second, to use the simulation to compare the commercial behavior of different car-sharing
companies and perform what-if analyses of new tariffs options. This is in line with the new
trend of car-sharing companies to diversify their offerings by introducing special rates according
to the business model of the mobility market.
Given a certain city, a set of tariffs, described in terms of price per driving minute, price
per parking minute (price paid by the customer if the car is parked during the rental period),
and price per km, customer preferences in terms of trips, trip types, and km traveled per year,
and a list of possible trips, our Monte Carlo simulation repeats the following overall process I
times.
Identify a set of potential routes.
Create Sscenarios with random demands, in term of customer trips, their temporal dis-
tribution, and type.
For each scenario s∈Sand until the km traveled per year are not reached,
16

–Extract a route from the routes list, assign a departure time according to the user
preferences, simulate it in terms of actual travel time, and apply to it the more
profitable tariff of the user type.
Given the scenario values in terms of costs paid to travel the km traveled per year, compute
the expected value of the cost.
Compute the distribution of the expected value.
In order to obtain the most reliable results of the Monte Carlo simulation, we perform a set
of tuning tests. The values for the parameters I(number of repetitions) and |S|(number of
scenarios) have been set, such that the standard deviation of the distribution of the expected
value is less than 1% of its mean. These values are I= 10 and |S|= 30.
The cost calculation for the utilization of car-sharing services mainly depends on the usage
time, distance traveled, and number of trips (as some companies charge a fixed base price in
addition to a price proportional to the distance travel). The period of utilization of the service
depends on the distances traveled, on the routes taken, and on the traffic conditions (which
influence the average speed in which the distances are covered), while the traffic conditions
depend on the routes considered in the study as well as on the time of day. In the following
subsections, we provide insight into the scenario definition process, user profiles, estimation of
travel times, and tariffs used in the simulation.
6.1. Definition of scenarios
We now present the results of the commercial behaviors of the different car-sharing compa-
nies operating in Turin. We chose Turin for our case study for the following reasons:
in order to correctly simulate car-sharing user profiles we need detailed traffic data.
Thanks to our collaboration with the Municipality (URBeLOG,2015) and to the sen-
sors network of 5T (a public company responsible for the monitoring of traffic in Turin),
real data on traffic are available at http://www.5t.torino.it/5t/;
Turin presents a high density of car-sharing companies and vehicles, with 1.6 car-sharing
vehicles every 1000 private cars, third Italian city for that ratio (Sharing Mobility Obser-
vatory,2016);
the city of Turin presents a high penetration of car-sharing services (Perboli et al.,2017a).
The city of Turin is serviced by four different car-sharing companies (Enjoy, Car2Go, Blue-
Torino, and IoGuido). A set of different routes was defined, ranging from 2.2 to 7 km, connecting
the main business districts, universities, train stations, cultural attractions, and residential ar-
eas. Turin was chosen as the test field for the evaluation of the economies of car-sharing due
to the presence of a broad sensor network, which measures traffic congestion in real time. Data
on the traffic patterns of the city were necessary in order to calculate the duration of trips
taken on different routes at different times of day. In the case of Turin, real data on traffic
are collected from 50 speed sensors in the city center and 100 distributed in suburban areas.
Data are gathered at different times of day, during one workweek, in order to build central
17

and suburban speed profiles (see the two circles in Figure 5, providing the distribution of the
actual sensors). The data of the mean vehicle speed, expressed in km per hour (km/h), are
accessible at five-minute intervals. We aggregated them into blocks of 30 minutes, for a total of
48 observations per day. The empirical speed profile distributions associated with the path, k,
between two points in the urban area, i and j, are then generated as inverse of the Kaplan-Meier
estimate of the cumulative distribution function (also known as the empirical cdf) of the speed
dataset, aggregated into blocks of 30 minutes. More details on the definition of speed profiles
and use of traffic data in a simulation environment are reported in Maggioni et al. (2014).
6.2. Definition of user profiles
The cost simulation considers three different user profiles: commuters, professional users,
and casual users. The first, defined as the commuter profile, represents individuals that might
use car-sharing services to commute between their residences and work places. Hence, their
trips are simulated including two different time slots: from 7 to 9am and from 5 to 7pm, aligned
to a regular working day. The second user profile, defined as professional, is represented by
individuals that might need a vehicle for work purposes during a regular working day. Hence,
their trips are simulated including three time slots: from 11am to 1pm, from 1pm to 3pm, and
from 3pm to 5pm. Finally, the third profile is defined as the casual user, who might use the
vehicle for different purposes at any time of day. Hence, the trips are simulated including all
time slots comprised in the simulation.
Finally, five different ranges of distance are considered for each of the user profiles in each of
the scenarios. The simulation computes the results for annual usage as 1000, 2000, 5000, 6000,
7000, 8000, 9000, 10000, and 15000 km.
6.3. Computation of trip times and overall costs for users
For each user, one route (among the defined routes) is randomly attributed to a time slot.
The trip time is then calculated, based on the route distances in the central and suburban areas,
and the average speeds in the center and suburban areas at the given time of day (randomly
attributed among the time slots of the selected user profile), as calculated in the definition of
traffic patterns. The parking period for each trip is also determined, based on the probability
and duration of parking, as defined in the user profiles. Finally, it is possible to calculate the
user costs, according to the utilization of each car-sharing company or private vehicle included
in the scenarios, and by using the most profitable tariff option associated with the user.
6.4. Tariffs
To compute the overall costs for a user, the prices and packages of each car-sharing operator
must be analyzed. Car2Go offers monthly minute packages of 120 or 300 minutes at discounted
rates for frequent users, so the cost calculation is optimized for the best possible combination of
minute packages per month for each customer. The minute rates of Car2Go and Enjoy include
at least 50 km of mileage. Given the fact that the longest route defined in the simulation has
a length of 7 km, additional costs per km are not incurred by users in the defined scenarios.
Single routes also do not justify the utilization of hourly tariffs. IoGuido has a different pricing
structure: customers must pay a minimum hourly fee (the minimum rental period is one hour,
18

although vehicles can be delivered earlier), in addition to a variable cost per km. The tariffs
refer to the simplest vehicle available in the one-way service (a Fiat 500 1.2L, the same model
offered by Enjoy). Among the three different tariffs provided by BlueTorino, we choose the
one with a fixed fee of 5 eper month (60 eper year) and variable fee of 0.19 eper minute.
Finally, the data referring to private vehicle costs are obtained from a database made available
at the website http://www.aci.it/ by ACI (Automobile Club Italiano), a National organization
that offers a wide range of public services, including a tool for calculating the costs of private
vehicle utilization. The data refer to a Fiat 500 1.2L, the same model offered by Enjoy and
IoGuido. To these costs, the additional parking fee should be added. Different tariffs exist in
any urban area; we decide to consider the cheapest one, equivalent to an annual fee of 200 ein
Turin (annual authorization for residents). The final prices are then calculated for each of the
users simulated for each user profile.
Tables 2and 3summarize the price components of these operators and costs of a private
vehicle.
Price Car2Go Enjoy IoGuido BlueTorino Private vehicle
components
Annual cost e29 (year 1) - e59 e60 e2620
Cost per min e0.29 (base price) e0.25 - e0.18 -
Parking cost see cost per minute see cost per minute - - -
Cost per hour e13.90 (not applied) e15 (not applied) e3.68 - -
Cost per km e0.29 (>50 km) e0.25 (>50 km) e1.08 (>100 km) - e0.23
Table 2: Costs of alternatives considered in simulation
Fixed costs Variable costs per km
Amortization e559.48 Amortization e0.066
Insurance e1929.00 Fuel e0.105
Taxes and fees e559.48 Tires e0.066
Maintenance e0.052
Total e2620.06 Total e0.232
Table 3: Estimated costs of private vehicle utilization
7. Simulation results
Analyzing the simulation results, the most interesting solutions from an economic point of
view vary according to the annual distance traveled. Figures 6,7, and 8report the annual
costs according to the user profile for the utilization of the car-sharing service of the companies
operating in Turin. These figures also show the annual costs for a private vehicle.
In the city of Turin, the usage of BlueTorino is always more cost effective than is that of the
other car-sharing operators, and it is more cost effective than are private vehicle for values lower
than 10000 km/year for the commuter and professional user profiles. The breakeven point with
the private vehicle is lower (8000 km/year) for the casual user profile. Despite having an annual
cost higher than those of the other operators, the lower variable cost allows BlueTorino to provide
cheaper services to consumers than can Car2Go and Enjoy. In particular, the breakeven point
between BlueTorino with Car2Go is set at about 170 km/year, while that between BlueTorino
19

and Enjoy is at about 300 km/year. Moreover, the pricing structure of BlueTorino is composed
by a fixed fee of 5 eper month, which discourages the occasional use of the service and, at the
same time, is low enough to be amortized with the usage (the breakeven point with the other
companies is reached at around 100 minutes of usage). The free-floating operators (Car2Go and
Enjoy) are more cost effective than are private vehicles for ranges lower than 4000 km/year, and
Enjoy is more cost effective than is Car2Go, due to its lower variable fee. However, the price
difference between Enjoy and Car2Go is marginal (in particular, for the lower ranges) and the
choice for the customers could be based on other factors of differentiation, such as perceived
quality of the service, vehicle models, and commercial partnerships.
The costs of IoGuido are steadily higher than those of the other operators. The reason is
in the different pricing structure, which consists of a minimum hourly fixed fee, in addition to
a fee per km. IoGuido could be more cost effective for other user profiles, not included in this
simulation, such as long-distance travelers (the distance fee decreases for longer distances) or
customers interested in longer rental times (not for a single trip). At the beginning of 2017,
IoGuido car-sharing service in Turin was not more operational, mainly because of significant
economic losses. Since new competitors had come to the market, the company lost its monopoly
over the Turin urban area, not being able to move toward the new free-floating service model.
Above the range of 10000 km/year for commuter and professional user profiles and of 8000
km/year for the casual user profile, the optimal choice is the private vehicle (considering a small
city car, similar to Enjoy’s fleet vehicles). In this case, the fixed costs of vehicle ownership are
amortized and the marginal costs are compensated by the distance covered by the users. For the
professional and casual user profiles, the results vary moderately. Although commuters have
routes concentrated on rush hours, with lower average speeds, professional and casual users
showed higher final costs of utilization; this effect is explained by the parking time included in
the rental for these user profiles, leading to higher costs that are not incurred by commuters,
by definition. Since, for private vehicle utilization, parking costs are modeled as fixed (as users
incurred the costs of annual parking permits), the costs related to private vehicles are not
sensitive to the differences between professional and casual users in the simulation. As a result,
for the casual and professional user profiles, a downshift could be observed in the minimum
range above which the utilization of a private vehicle is more economically efficient. In these
cases, using a private car becomes the optimal cost alternative between 6000 and 7000 km per
year. In Table 4we summarize the simulation results, showing for each user profile which is the
best operator, according with the annual distance travelled.
It is interesting to see how BlueTorino is using a mix of aggressive pricing with a green vision
of car-sharing, having the double effect of straightening its positioning in the catchment area
and pushing the idea that having electric mobility is possible. This is crucial for the owners of
BlueTorino, the Bollor´e Group, who made large investments in the production of electric vehicles
and are trying to standardize and dominate the future market of charge stations. Actually,
BlueTorino is becoming a perfect example of how revenue cannot be the first objective of a
company. If the company has success, as they already have in France, and makes its charging
stations unique in the large and medium cities, this will give to the Bollor´e Group a great
competitive advantage in the next 10 years, also contributing to a change in the behaviors of
20

citizens. One of the main results is the higher cost effectiveness of BlueTorino compared with
that of the other operators, given by the lower variable cost that allows customers to amortize
the annual fixed charge of 60 e(5 eper month). In this case, private vehicles become more cost
effective for ranges higher than 10000 km/year, for the commuters and professional user profiles,
and higher than 8000 km/year, for the casual user profile. After these amount of kilometers,
the fixed cost related to vehicle ownership is amortized and the marginal cost is compensated
by the distance covered by the users. BlueTorino’s tariff choice is partially in contrast with the
business behavior of the car-sharing market, which discontinued with fixed costs in the past
decade. On the contrary, the tariff scheme of BlueTorino, as shown by its preliminary economic
results in Turin, shows how a limited fixed monthly fee is preventing the casual user. This
behavior is similar to the recent tariff schemes used in the mobile market, and it avoids the
problem of customers stopping usage of the service. Fleet size is the main asset of a car-sharing
company, in order to meet the customer demand and not incur imbalances within the covered
area. The best players rely on large-scale operations with large fleets to address this question,
trying to minimize fleet-management efforts and allowing for the spontaneous use of the service
by customers, to reposition the largest percentage of vehicles, but fleet-size planning becomes
very difficult if a large portion of customers is not using the service after the initial period. This
is a typical situation in a market green field, where different companies are entering and offering
discounted prices in the early stage.
According to the preliminary results collected in the city of Turin by means of a large survey
from the beginning of car-sharing to now, this change is underway. In particular, there is a need
of more flexible and user-specific tariffs (Perboli et al.,2017c). In particular, professional users
are requesting new ad-hoc tariff schemes. However, such an approach requires the availability
of new tools for supporting the decision-making process.
8. Conclusions and future directions
In this paper, we present a joint analysis of business models (qualitative analysis) and sim-
ulation (quantitative analysis), with the aim to help the strategic choices of the car-sharing
operators. The comparison of the operators’ business models shows that all the companies
share value propositions inherent to the car-sharing concept, offering an alternative for mobility
with low environmental impact, complementary to the available public and private modes of
transportation and, generally, economically efficient when compared to car ownership. More-
over, it emerges that Bollor´e Group, with BlueTorino car-sharing service, wants to impose its
standards on charging stations, since no standard is currently present in Italy.
Moreover, partnerships with car manufacturers (mainly for Car2Go and Enjoy) highlights
the vehicles of the car brand involved in the service. This is the so called mobility-as-a-service
paradigm, towards which are moving in the last years many manufacturers research centers
(GM,2017).
However, the company success in delivering these values to their customers depends on
their operational characteristics. The service model adopted is the main difference between the
analyzed companies; since the option for traditional roundtrip car-sharing (adopted by IoGuido)
lessens the complexity of fleet management, this form of operation provides less flexibility for
21

km/year → < 2000 2000-4000 4000-6000 6000-8000 8000-10000 >10000
Commuter user
profile
Best choice BlueTorino BlueTorino BlueTorino BlueTorino BlueTorino Private vehicle
Other choices (sorted)
Enjoy Enjoy Enjoy Private vehicle Private vehicle BlueTorino
Car2Go Car2Go Car2Go Enjoy Enjoy Enjoy
Car City Club (ICS) Private vehicle Private vehicle Car2Go Car2Go Car2Go
Private vehicle Car City Club (ICS) Car City Club (ICS) Car City Club (ICS) Car City Club (ICS) Car City Club (ICS)
Casual user profile
Best choice BlueTorino BlueTorino BlueTorino BlueTorino Private vehicle Private vehicle
Other choices (sorted)
Enjoy Enjoy Enjoy Private vehicle BlueTorino BlueTorino
Car2Go Car2Go Car2Go Enjoy Enjoy Enjoy
Car City Club (ICS) Private vehicle Private vehicle Car2Go Car2Go Car2Go
Private vehicle Car City Club (ICS) Car City Club (ICS) Car City Club (ICS) Car City Club (ICS) Car City Club (ICS)
Professional user
profile
Best choice BlueTorino BlueTorino BlueTorino BlueTorino BlueTorino Private vehicle
Other choices (sorted)
Enjoy Enjoy Enjoy Private vehicle Private vehicle BlueTorino
Car2Go Car2Go Car2Go Enjoy Enjoy Enjoy
Car City Club (ICS) Private vehicle Private vehicle Car2Go Car2Go Car2Go
Private vehicle Car City Club (ICS) Car City Club (ICS) Car City Club (ICS) Car City Club (ICS) Car City Club (ICS)
Table 4: Suggested operator based on annual traveled distance and user profile
22

users, as they must start and end their journey at the same parking spot and pay for the service
during the entire time of rental. On the other hand, the free-floating model provides customers
with the greatest flexibility, allowing them to locate, optionally reserve, and then access an
available vehicle directly on the street, and use it for any period of time.
Analyzing the simulation in the city of Turin, the main result is the higher cost effectiveness
of BlueTorino compared with that of the other operators, given by the lower variable cost,
which allows customers to amortize the annual fixed charge of 60 e(5 eper month). Private
vehicles become more cost effective for ranges higher than 10000 km/year for the commuter and
professional user profiles and higher than 8000 km/year for the casual user profile. After these
amount of kilometers, the fixed cost related to vehicle ownership is amortized and the marginal
cost is compensated by the distance covered by the users.
In our opinion, simulation tools need to be factually integrated in the planning and testing
phases of new pricing strategies (e.g. different fees in different periods of the day, or for different
user profiles), even if further developments are required to use this tool in cities without a
network of sensors for traffic monitoring. In fact, the traffic congestion and, consequently, travel
time play a key role in the economies of car-sharing services and, thus, accurate forecasting
is required. Future research directions should consider approximations of traffic congestion,
obtained by means of extreme value theory (Perboli et al.,2012;Tadei et al.,2012), as well as
more complex user behaviors and tariff schemes. Moreover, the choice mechanisms of the final
users could be embedded into the simulation tool, as made in the airline market (Perboli et al.,
2015).
Acknowledgments
Partial funding for this project was provided by the Italian University and Research Ministry
(MIUR), under the UrbeLOG Project-Smart Cities and Communities, and the Natural Sciences
and Engineering Council of Canada (NSERC), through its Discovery Grants program. While
working on this paper, prof. Guido Perboli was Director of the ICT for the City Logistics and
Enterprises lab of Politecnico di Torino (ICT for City Logistics and Enterprises,2016).
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26

Key Partnerships
 Europcar
 Local governments
 Company customers
(refueling agreement)
 Insurance companies
 Fuel distribution
companies
Key Activities
 Car rentals
 Vehicles maintenance
 Fleet management
 Customer service
 Marketing
Value Proposition
 Free-floating car sharing
service with a large
scale fleet
 Innovative and
environmental friendly
transportation service
 Flexibility and mobility
 Convenience, usability
and accessibility of
vehicles
 Smart ForTwo (gasoline
and electric powered)
vehicle fleet
Customer Relationships
 Automated services
through the website and
application interfaces
 No permanent
engagements
Customer Segments
 Private users
- Frequent clients
- Occasional clients
- Students
 Corporate clients
Key Resources
 Vehicle fleet
 Service team
 Integrated system,
website and application
 Designated parking
spots (where applicable)
Channels
 Website
 Smartphone application
 Customer service call
center
 On site marketing
campaigns and
information points
Cost Structure
 Vehicle fleet acquisition
 Maintenance
 Fueling and cleaning vehicles
 Personnel costs and customer services
 Insurance contracts
 Other expenses related to improper use of the service
 Municipality taxes
Revenues
 Fixed subscription fees (only upon registration of new users)
 Rental fees (per minute, hour or daily rate)
 Extra fees per kilometre (above the included mileage per trip)
Figure 1: Business Model Canvas of Car2go
27

Key Partnerships
 ENI
 Trenitalia (Italian train
operator)
 FCA (vehicle supplier)
 CartaSi (credit card
company)
 Other commercial
companies and
suppliers
 Local municipalities
 Insurance companies
Key Activities
 Car rentals
 Vehicles maintenance
 Fleet management
 Customer service
 Marketing and
establishing new
partnerships
Value Proposition
 Free floating car sharing
rentals
 Fiat 500 fleet (design
appeal, iconic car, four
sits)
 Flexible, environmental
friendly and economical
mobility service
 Integration with train
services
Customer Relationships
 Automated services
through the website and
application interfaces
Customer Segments
 Private users
- Occasional users
- Frequent users
 Corporate clients
- Trenitalia loyalty
program clients,
including corporations
Key Resources
 Vehicle fleet
 Service team
 Integrated system,
website and application
Channels
 Website
 Smartphone Application
 Customer service call
center
 Co-marketing with
Trenitalia
Cost Structure
 Vehicle fleet acquisition
 Maintenance, fueling and cleaning vehicles
 Personnel costs and customer services
 Insurance contracts
 Municipality taxes
 Other expenses related to improper use of the service
Revenues
 All-inclusive rental fees (per minute, hour or daily rate)
 Extra fees per kilometre (above the included mileage per trip)
 Cross-selling (Trenitalia partnership)
Figure 2: Business Model Canvas of Enjoy
28

Key Partnerships
 Municipality
 Car Sharing Initiative
(ICS) and Italian
Ministry of
Environment
 Car manufacturers
(FCA), fuel
distributors, insurance
companies
 Retail companies,
universities and other
promotion partners
Key Activities
 Car rentals
 Vehicles maintenance
 Fleet management
 Customer service
Value Proposition
 Mobility alternative,
integrated with other
public transportation
modes
 Economical, accessible
and environmental
friendly service
 Traditional and one-way
car rentals
 Varied fleet of vehicles,
for different customer
needs
Customer Relationships
 Self-service automated
services through the
website and application
interfaces
 Optional call-center
service
Customer Segments
 Private users
 Corporate clients
 Public entities
Key Resources
 Vehicle fleet
 Service team
 Integrated system,
website and application
 Exclusive parking areas
Channels
 Website
 Smartphone application
 Customer service call
center
Cost Structure
 Vehicle fleet acquisition
 Maintenance
 Fueling and cleaning vehicles
 Personnel costs and customer services
 Insurance contracts
 Other expenses related to improper use of the service
The company is partially financed by the Italian Ministry of the
Environment
Revenues
 Annual subscription fees (or optionally an activation fee per use)
 Fixed rental fees (hourly or daily, according to the period of the day
and type of vehicle chosen)
 Fees per traveled kilometre
Figure 3: Business Model Canvas of Car City Club (IoGuido)
29

Key Partnerships
• City of Turin
• Bollorè Group
• Bluecar
• Pininfarina
• CECOMP
• batScap
Key Activities
• Car rentals
• Vehicles maintenance
• Fleet management
• Customer service
Value Proposition
• First full electric car
sharing service in Turin
• One way point-to-point
rentals
• Efficient and low
environmental impact
mobility alternative,
complementary to
public transportation
services
• Flexibility, availability
and economic efficiency
when compared to car
ownership
Customer Relationships
• Automated services
through the website and
application interfaces
• Customer service call
center
Customer Segments
• Private users
- Frequent users
- Occasional users
- Tourists
- Young drivers
- Households
Key Resources
• Vehicle fleet
• Charging stations
• Integrated information
system, website and
application
• Management and
service team
Channels
• Website
• Smartphone application
• Customer service call-
center
Cost Structure
• Vehicle fleet acquisition
• Installation of charging stations
• Maintenance, cleaning and recharging
• Development and maintenance of website, app and information
system
• Personnel costs and customer services
• Insurance contracts
• Other expenses related to improper use of the service
Revenues
• Private user plans
- Subscription fees
- Rental fees (per minute)
Figure 4: Business Model Canvas of BlueTorino
30

Figure 5: Distribution of central (dark gray circle) and suburban (light gray circle) speed sensors in the city of
Turin, Italy. Figure taken from Tadei et al. (2017).
Figure 6: Annual costs for commuter user profile in Turin.
31

Figure 7: Annual costs for casual user profile in Turin.
Figure 8: Annual costs for professional user profile in Turin.
32