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Study ordered by City on the Move and conducted at INRETS by Diallo Mamadou Sanoussi under the supervision of Laurent Hivert and Francis Papon. PARC-AUTO PANEL: WHO RENTS? WHO SHARES?. Francis.Papon@INRETS.fr Laurent.Hivert@INRETS.fr. The « car & owner » harmonious couple
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Study ordered by City on the Move and conducted at INRETS by Diallo Mamadou Sanoussi under the supervision of Laurent Hivert and Francis Papon PARC-AUTO PANEL:WHO RENTS?WHO SHARES? Francis.Papon@INRETS.fr Laurent.Hivert@INRETS.fr
The « car & owner » harmonious couple Nearly all adults who can drive and afford a car do own a car and drive it most of the time But, excessive solo driving threatens sustainability Constant annual mileage per car =>reduce car ownership Unfaithfulness: driving not my own car Car sharing clubs: recent and small scale Car rental: well established economic activity Car sharing within households: wide-spread habit Breakingthe « car & owner » paradigm Who rents? Who shares?
Household car sharing favoursalternative transport modes Source: Papon, 2001 from 1994 French transport survey data •strong relationship between potential drivers and actual drivers •shared drivers use other modes 72% more than individual drivers Who rents? Who shares?
Tissier-Desbordes, Cova & Manceau, 2005, Projet Possession/Location, City on the Move International Fr, It, comparison De, UK Sociologists’ and economists’ review Highlight etymology Frequently rented articles analyse Consumers survey and companies interview. In France, the car rental market scored 1.6 billion euros in 2002; "rent-a-car" societies, insurance companies, car manufacturers seem very interested in this market evolution. Car rental is marginalin transport research Who rents? Who shares?
Who rents? How often, long? Which trend? Which households? How old, high, rich? Where? Which owned cars? When, why, how? How to model? Who shares? Which cars? Whether more licences? Which households? How old, high, rich? Which drivers? Which gender? Which trend? How to model? Objectives Who rents? Who shares?
Car rental Frequency and trend Household features Licences and cars Context Model Car sharing Licences and cars Wages Gender issues Age groups Trend and model Overview Data Conclusions Who rents? Who shares?
Annual postal surveys conducted by SOFRES Panel of 10 000 French households since 1983 Renewal rate of the sample by 1/3 per year Weights: region, agglomeration size, number of persons in hh, age, occupation of head Representative of French households and cars About 100 questions: Car ownership Car characteristics Main and secondary users Previous car characteristics Car use behaviour Attitude towards automobile Opinion vis-à-vis car brands Purchasing intents The Parc-Auto database Who rents? Who shares?
Car rental: “During the last 12 months, did you — or another person from your home — rent a car in France for personal purpose?” “Yes.” 2308 (4.2%) Sample 1994-2001: 54 742 households-years Car sharing: “Is this car occasionally used by other persons?” (from household or not) “Yes.” 3256 (40%) Sample 2001: 8177 cars Two key questions Who rents? Who shares?
Renting households: no trend Proportion of households renting a car during the year 4,22% Who rents? Who shares?
Two-thirds are one-time renters Annual renting frequency Who rents? Who shares?
Most hires are short(short = 1 to 4 days; long = 5-30 days) Renting frequency and length Who rents? Who shares?
29% of renters in year t rent again in t+1 51% of renters in both year t and year t+1rent again in year t+2 And so on For a minority of renters, renting is a sustained habit Multi-renters rent more often next year Car rental is occasional Who rents? Who shares?
Renters earn high income(over 200 000 francs) renters all Distribution of households by income group Who rents? Who shares?
Renters live in the Paris area all renters Distribution of households by habitat Who rents? Who shares?
Renters are middle-aged hhh* renters all *hhh: household head. Distribution of hhh age groups Who rents? Who shares?
Renters have higher positionand more active hhh Distribution of household head occupation renters all Who rents? Who shares?
Households with an even number of adults rent more Proportion of households renting a car during year Considered age groups Number of persons in household Who rents? Who shares?
Renting householdshold more licences all renters Distribution of households by the number of driving licences Who rents? Who shares?
One car households rent lesscar ownership not significant all renters Distribution of households by car ownership Who rents? Who shares?
Renters own multiple, young, large engine, high quality cars Proportion of renting households Number of cars Who rents? Who shares?
Those moving house rent a car twice more often (7.6% vs 4.2%) Those renting a van rent a car 2.5 times more often and vice-versa, but confusing question Among van renters, last renting context 13% of renters vs 7% of allmove house during year Who rents? Who shares?
Less significant variables (Backward elimination): Number of working persons Number of adults Area type Number of cars Region Most significant variables (Forward or Stepwise selection): Income Habitat Hhh age Hhh position Number of persons in hh Number of licences Number of young cars Number of large engine cars Number of persons over 15 Number of high quality cars Modelling car rental Who rents? Who shares?
Selected variables yieldinglow or high renting activity Probability of renting as compared to reference Who rents? Who shares?
Who rents? Summary Renting households are mainly working, high income, middle-aged households, living in the core of big cities, and in particular in Paris. Most of them have several driving licences and recent, high power, high quality cars. Car rental is mainly an occasional practice. Yet for a minority of renters, it is a sustained habit: 30% of households renting a car on year n rent again on year n+1. Who rents? Who shares?
Only driversnot passengers From householdor outside During the last 12 months Different aspects: Loan of a car-regular or not-different trips or purposes Division of driving e.g. long distance A fuzzy concept of sharing Who rents? Who shares?
More licences, more sharingOne car shared the least or the most Proportion of shared cars Number of licences Car rank * as defined by respondant Who rents? Who shares?
Hh with more licences than carsown 41% of shared cars vs23% of all cars Shared cars All cars Distribution of cars by car rank and the number of licences Who rents? Who shares?
More licences, more sharing Licence structure Proportion of shared cars Size of bubble proportional to number of cars in fleet Who rents? Who shares?
Given licence structure, sharing drops with car number* & rank Number of cars in hh Overbooked cars Secondary cars (S) are to the right of main cars (M) M S M Proportion of shared cars S S M *except who share more when own two cars Size of bubble proportional to number of cars in fleet Don’t touch my car Who rents? Who shares?
High income hh share more but mainly because they own more cars and hold more licences Proportion of shared cars Household income 48% 40% Car rank and number of licences 28% of their cars are shared Who rents? Who shares?
No significant sharing disparity according to position Proportion of shared cars Position of hhh Car rank and number of licences Who rents? Who shares?
When more work, sharing increases, but decreases given car-licence structure Proportion of shared cars Number of working persons 50% 44% 38% 33% Car rank and number of licences Overall sharing rate Who rents? Who shares?
Partners share more than heads as main users* (47% vs 38%) Proportion of shared cars Children share less their cars Main user Car rank and number of licences *but are less often main users of main cars Who rents? Who shares?
Female main users share more Proportion of shared cars Main user gender Car rank and number of licences Who rents? Who shares?
Gender prejudiced driver role Other car Female Main user Main car Female Other user Same pattern with more other drivers Women are more often single Man main user Who rents? Who shares?
Female household headsshare more Proportion of shared cars House hold head gender Car rank and number of licences Who rents? Who shares?
The youngest household heads share the most Proportion of shared cars Age of household head Car rank and number of licences Who rents? Who shares?
40-64 years old share more Proportion of shared cars Main user age Car rank and number of licences Who rents? Who shares?
Car sharing is decreasing Proportion of shared cars Cross-section trend Proportion of multi-car ownership Longitudinal analysis: Car sharing is a regular practice •4 cars out of 10 are shared 3 of them are shared again next year •6 cars out of 10 are not shared 1 of them is shared next year Who rents? Who shares?
Less significant variables (Backward elimination): Area type Number of adults Head position Number of persons over 15 Number of persons in hh Existence of public transport at proximity Most significant variables (Forward or Stepwise selection) Number of licences Number of cars Income Main user Main user gender Head gender Number of working persons Region Head age Main user age Modelling car sharing Who rents? Who shares?
Who shares? Summary Households with more licence holders than cars share the most: about three quarters of them share their cars. On the contrary, single driver-single car households have less opportunity to share: only 15% share. Car sharing shed light on the gender role within households: while 58% of the main users of the shared cars are male, 55% of secondary users are female. Car sharing is mainly a regular practice: four cars out of ten are shared on year n, three of them are shared again on year n+1. Who rents? Who shares?
ConclusionsWho rents? Who shares? Who cares? • Self established behaviour within households. • Diverse situations that cannot be easily handled by straightforward classifications. • The car cannot be reduced to a personal object. • Car sharing also carries strong links with the issue of car dependency. • Sifting car availability and choice universes may be useful for fitting disaggregated models of sharing. Who rents? Who shares?