Investigating the determinants of a Peer-to-peer (P2P) car sharing. The case of Milan

1
Investigating the determinants of a
Peer-to-peer (P2P) car sharing. The case of
Milan

• Ilaria Mariotti
• Paolo Beria
• Antonio Laurino
• DAStU, Politecnico di Milano

SIET 2013 Venezia, September 18th 20th , 2013

2
STRUCTURE

• Aim
• Literature review on P2P
• Data and methodology
• Descriptive statistics
• Econometric analysis
• Discussion and conclusions

3
AIM

• Investigate the main determinants to join a P2P
  car sharing system by means a descriptive
  statistics and two discrete choice models
  binomial logit model and multinomial logit model

1,129 Milan citizens have been surveyed (Green
Move project).
4
Literature review (1)

• Ex-post analyses on Car Sharing (CS) prevail
• Main determinants to join CS
• density of users aged 25 45, single or living
  in small households
• well educated with an income higher than the
  average
• cost sensitive
• environmentally conscious
• good public transport service
• CS mainly used for recreation/social activities

5
Literature review (2)

• Literature on P2P system is scanty
• Hampshire and Gaites (2011) emphasise the higher
  accessibility that P2P scheme could entail, in
  particular in lower density areas, thanks to the
  almost total absence of the upfront costs that a
  traditional CS operator has to bear to buy its
  fleet.
• Hampshire and Sinha (2011) analyze the main
  trade-off of balancing car utilization with
  reservation availability.

6
Data and methodology

• Dataset Green Move survey conducted in 2012
  among the inhabitants of the municipality of
  Milan (1,129 respondents)
• The probability to undertake a P2P carsharing is
  investigated by means of a descriptive
  statistics, which results are corroborated by a
  binomial logit model and a multinomial logit
  model

7
Dependent variable
8
Explanatory variables
Variable Description
Gender Dummy variable 1 if male, 0 if female.
Age Age of the respondent
Education Dummy variable 1 if the respondent achieved a bachelor degree, 0 otherwise
N. of owned cars Number of cars owned by the family
Oil price Dummy variable 1 if the respondent has changed his/her travel patterns, 0 otherwise.
District of residence District where the respondent lives. Dummy variable.
Modal choice LPT, Bike, Foot, Motorcycle, Car (driver), Car (passenger) Six dummy variables suggesting the main modal choice adopted by the respondent.
Daily travel by car for reaching the workplace,or the LPT stop moving within the neighbourhood or outside leisure in the city, other motives Six dummy variables underlying why the respondent uses the car daily or very often.
Car sharing member Dummy variable 1 if the respondent is or has been member of CS services, 0 otherwise.
Area C tool and travel behaviour change Dummy variable 1 if the respondents have reduced the car use consequently the Area C introduction, 0 otherwise
Socio economic
Travel behaviour
Green Attitude
9
Descriptive statistics (1)

• 53.4 potential sharers

10
Descriptive statistics (2)
11
Descriptive statistics (3)

• Respondents travel behavior

9 of the potential sharers are or have been
members of the Milan CS vs. 2.5 of the non users
12
Binomial logit model
13
Results Group 1
GROUP 0 Those not interested to join a P2P CS
system
14
Results Group 2
GROUP 0 Those not interested to join a P2P CS
system
15
Results (1)

• The probability to join a P2P CS is positively
  and significantly related to
• users education (bachelor degree),
• car ownership (more than two cars),
• travel behaviour (LPT and bike),
• CS membership (previous or present),
• cost sensitiveness (i.e. oil price increase).

16
Results (2)

• When comparing the users willing to share their
  own car with all members of the P2P system
  (confident shares), it results that they tend to
  be
• male,
• use the car daily to reach the LPT stop,
• have reduced the car use because of the Area C,
• are less willing to live in zone 9.
• While, those willing to share their own car only
  with a selected group of people, tend to be
• younger,
• use the bike to travel,
• are less willing to live in zone 7.

17
CONCLUSIONS

• Relevance of the three groups of determinants
  socio-economic, travel behavior and green
  attitude.
• Potential users are sensitive to CS systems
  being or having being members of the Milan CS ,
  and are cost-sensitive (i.e. oil price increase
  and Area C policy tool). Besides, they prefer to
  ride the bike or use the LPT to travel.

18
Thank you

• Questions and suggestions are welcome

Ilaria Mariotti DAStU Politecnico di Milano
ilaria.mariotti_at_polimi.it