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Car-Sharing: Where and How It Succeeds (2005)

Chapter: Chapter 3 - Market Analysis

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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Suggested Citation:"Chapter 3 - Market Analysis." National Academies of Sciences, Engineering, and Medicine. 2005. Car-Sharing: Where and How It Succeeds. Washington, DC: The National Academies Press. doi: 10.17226/13559.
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Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Car-Sharing: Where and How It Succeeds Page 3-1 CHapter 3. Market analySIS Car-sharing can be called a niche product. At its December 2004 level of 61,652 members, it attracted just 0.02% of the entire US popula- tion, 0.03% of US licensed drivers, and the same proportion of urban residents. Even in countries where it has been established far longer, such as Switzerland, car-sharing membership still accounts for less than 1% of the population and 1.4% of driver’s license holders. In Germany, market share at the end of 2001 was just 0.12% of licensed drivers (Schwieger, 2004). That said, car-sharing appears to have the potential to serve a far more significant proportion of the population in the United States among targeted demographic groups, and in particular neighbor- hoods. This potential can be realized by understanding the market niches where car-sharing is most attractive. This chapter focuses on identifying and analyzing these niches, at least at this relatively early stage in the development of the concept. They can be characterized in two broad ways: • Demographic Markets – the demographic groups that are most likely to join a car-sharing program • Geographic Markets – the geographic neighborhoods where car-sharing vehicles can be placed to best effect Obviously, these factors are interrelated, as the demographic char- acteristics of users will, to some extent, be correlated with certain features of the wider neighborhood. However, there are important differences. Demographic markets primarily refer to the “micro” characteristics of car-sharing users, while the geographic markets re- fer to the “macro” characteristics of the neighborhood as a whole. This chapter first discusses the different demographic markets to which car-sharing appeals, and the motivations for members to join. It presents findings from an internet survey and focus groups of car-sharing members, which examined their demographics, travel preferences, and other characteristics, including factors that moti- vated them to join car-sharing organizations. Each section concludes with a review of findings from existing literature.

Chapter 3 • Market analysis September 2005 Page 3-2 The second section analyzes the geographic market settings of car-sharing, in terms of the types of neighborhoods where car-sharing has been intro- duced. It provides a qualitative analysis — based on the existing literature, media reports and identification of existing locations — and a quantitative analysis of the demographic and physical characteristics around each car- sharing vehicle location (“pod”). Finally, this chapter reviews some previous research forecasting the poten- tial growth of car-sharing and suggests lessons that should be learned and applied to the research results presented here. 3.1 Demographic Market Segments attracted to Car- Sharing Market segmentation is the identification of distinct groups of customers who share specific characteristics and who are likely to exhibit similar purchasing behavior. Market segmentation can be used to highlight patterns of demo- graphic, spatial, behavioral, and attitudinal characteristics shared by persons who are currently using car-sharing services. These patterns demonstrate which kinds of persons (groups of customers, or market segments) are most likely to be attracted to car-sharing services. These persons can then be the focus of targeted marketing campaigns through which car-sharing operators can position their products and services by developing specifically tailored marketing strategies to appeal to the selected target markets. TCRP Report 36 notes that market segmentation can be used to “improve your agency’s competitive position and better serve the needs of your cus- tomers.” For the transit industry, market segmentation is said to be capable of providing (Elmore-Yalch, 1998): • Increased ridership • Improved share of mode choice • New customers • Better customers • More satisfied customers • Potentially more “profitable” marketing and service opportunities Market segmentation offers the same potential benefits for car-sharing or- ganizations and their partners.

Car-Sharing: Where and How It Succeeds Page 3-3 Methodology Web-Based Survey For this study, a web-based survey of current car-sharing members (ap- proved by the study’s Project Panel) was conducted in May, June, and July of 2004. The survey questions are provided in Appendix C. All but one of the large car-sharing companies in the United States and Canada encour- aged their members to participate in this survey. (Zipcar, one of the two largest car-sharing companies in the United States, chose not to participate in this survey. Based on information received from Zipcar, and because it is believed that their membership and practices are not substantially different from those of other operators, there is no reason to believe that their lack of participation altered the results of the survey in any specific way.) Because car-sharing is a highly competitive private enterprise (at least in some metropolitan areas), the study team was not provided lists of car- sharing members. Instead, participating car-sharing companies contacted some or all of their members by mail or e-mail and encouraged them to participate. The members contacted were free to participate or not; if they decided to participate, they were instructed to connect to a specific website. No follow-up contacts were made with members who did not participate. Anyone who completed the survey was eligible to be one of five winners of a US$50 credit on their next car-sharing bill. Use of this methodology means that the study team did not control how respondents were selected from or contacted by each company, and there- fore cannot verify that the respondents are statistically representative of the members of each company. However, we do believe that the companies who participated chose potential respondents in a fashion which accurately represented their entire membership. This methodology obviously focuses on individuals who are Internet users, possibly slighting other car-sharing members who are not computer users. But most car-sharing companies now do the vast majority of their reservations over the Internet, so use of the Internet to survey members should not have introduced any significant bias.

Chapter 3 • Market analysis September 2005 Page 3-4 Results Six companies (four of which were located in the United States) had more than 85 of their members respond to the web-based survey. Nine car-shar- ing companies, five in the United States and four in Canada, had 10 or more members respond, as shown in Exhibit 3-1. Three or fewer responses were received from members of five additional companies. (Thirteen respondents were members of other unidentified companies.) A total of 1,340 complete and valid responses were received, representing nearly 11% of those members contacted by their companies for this survey and almost 5% of the membership of the participating companies. (The majority of members who were not contacted are likely to be inactive ones.) While these response rates are not atypical for Internet surveys using simi- lar methodologies, some caution is advisable in interpreting the results of any survey with response rates in this range because of the possibility that non-respondents may differ from the respondents in ways that are not obvious. Most of the respondents (978) lived in the United States; 362 lived in Canada. The average respondent had been a member of a car-sharing organization for 19.5 months (the median membership period was 15 months). Exhibit 3-1 Companies with More Than 10 Respondents to Car-Sharing Member Survey Company Location AutoShare Toronto, Ontario Boulder CarShare Boulder, Colorado City CarShare San Francisco, California Communauto Quebec City, Montréal, Gatineau and Sherbrooke, Quebec Flexcar Seattle, Washington; Portland, Oregon; Los Angeles and San Diego, California; and Washington, DC PhillyCarShare Philadelphia, Pennsylvania Roaring Fork Valley Vehicles Aspen, Colorado Victoria Car Share Co-op Victoria, British Columbia Vrtucar Ottawa, Ontario

Car-Sharing: Where and How It Succeeds Page 3-5 Focus Groups Focus groups of car-sharing members were held in Boston, San Francisco, and Washington, DC. Five 90-minute focus groups were held with current members in January, February and March 2004. One 90-minute group was held with former or inactive members in September 2004. Participants were recruited from member lists supplied by Flexcar (two groups), City CarShare (two groups) and Zipcar (two groups). Fifty-six persons participated in a focus group. Each focus group member was paid $50 for their participation. Audio tapes were made of each session and the sessions were transcribed. Focus group discussions proceeded according to a Moderator’s Guide that included questions on travel using car-sharing (including reasons for using car-sharing and for joining car-sharing, and how life changed for them as a result of using car-sharing); their assessments of the most attractive and least attractive features of car-sharing; what they thought about auto ownership; and their recommendations for improving car-sharing. Participants were instructed not to discuss the benefits or problems associated with particu- lar car-sharing companies. A copy of the Moderator’s Guide is included in Appendix C. Focus group participants tended to be extremely positive about their car- sharing experiences, even those who were not currently using car-sharing services. Findings from the focus groups are included in this chapter and in Chapter 4. Demographic Characteristics of participants Those responding to the web-based survey reported the following demo- graphic characteristics: • Age: The mean age of the respondents was 37.7 years; the median was 35 years. (Note that, due to insurance issues, the minimum membership age allowed by most car-sharing companies is 21.) The lowest age reported was 20; the highest was 75. Thirty-nine percent of the respondents were in the 25 to 34 year old age group; 27.4% were in the 35 to 44 year old age group. Canadians were overrepresented in the 25 to 34 year old age group; US members were overrepresented in the much smaller age group of persons under 25 years old. • Income: Half of the respondents reported annual household incomes of $60,000 a year or more. Thirteen percent reported annual incomes of $30,000 or less; 18% reported annual incomes of $100,000 or more. Incomes were higher in the US: 20% of the members reported incomes over $100,000 per year, while 12 % of

Chapter 3 • Market analysis September 2005 Page 3-6 the Canadian members reported such incomes. Canadian mem- bers were more overrepresented in the income groups between US $20,000 and $60,000 per year, and US members were overrepre- sented in the small group of members with incomes under $10,000 per year. • Education: A substantial focus on the highest education levels, with 35% holding a Bachelor’s degree and 48% reporting some post-graduate work or an advanced degree. Only 2% of these respondents had less than some college education. As expected, respondents with the highest education levels had higher income levels than average. There were no significant differences between US and Canadian members in terms of their years of education. • Gender: Slightly more women than men responded to the sur- vey, by a margin of 55% to 45%. However, 52% of the Canadian respondents were male, while 43% of the US respondents were male. Women were more likely to have been involved in post- graduate work than the men in our sample. • Race/Ethnicity: Eighty-seven percent were white or Caucasian; 6% were Asian; 4% were “other”; and 4% were black. Three per- cent were Hispanic. • Household size: Sixty-four percent lived with at least one other person; the average household size was 2.02 persons. Children were present in 24.4% of households. Canadian car-sharing mem- bers were more likely to live with someone else by a ratio of 71% to 61% for US members. • Auto ownership: Overall, 72% of the respondents lived in house- holds with no cars, but 87% of the Canadian members lived in households with no cars, while 66.8% of the US members lived in households with no cars. Thus, the car-sharing members responding to the web-based survey had the following characteristics in relation to car-sharing members in other studies: • Their median age was identical to those in other studies. • Their incomes are definitely at the higher end of the scale, perhaps even higher than reported in other studies. • Their educational levels are definitely at the higher end of the scale, perhaps even higher than reported in other studies. • These respondents were slightly more often female than respon- dents in other studies. • Racial characteristics and household sizes were essentially the same as those reported in other studies.

Car-Sharing: Where and How It Succeeds Page 3-7 Thus, the demographic information from our internet survey appears to be quite similar, although not identical, to findings from previous studies. This study employed an internet survey of car-sharing members, which means that respondents were self-selected from contacts originating from the car- sharing companies. It is possible that the results of this survey overrepresent findings from members with higher income and educational levels, since such persons are more likely to own and use personal computers. Offsetting this hypothesis is the fact that many car-sharing companies now strongly promote internet scheduling and reservations. Since actual membership characteristic data are closely held proprietary information, it is not possible to ascertain how closely the survey results represent the actual members of these private companies. Members of specific car-sharing companies had somewhat different demo- graphic characteristics than the averages noted above. It is not clear whether these differences are due to corporate marketing strategies, the demograph- ics of specific localities, or some combination of these and other factors. It is also not certain that the demographic characteristics reported accurately represent the demographic characteristics of all members associated with a particular company. Reported demographic characteristics for companies with the largest numbers of respondents are shown in Exhibit 3-2. More than 85 responses were received from each of these companies.

Chapter 3 • Market analysis September 2005 Page 3-8 Exhibit 3-2 Reported Demographics of Car-Sharing Companies Car-sharing company Demographic characteristics more frequent to that company than to all respondents in general Company A Age 25 – 34 Live with someone Males Few car owners Company B Age 35 – 44; not age 45 – 54 Females Bachelor’s degrees Incomes $75,000 and above More grocery shopping trips Company C Age 25 – 34 Live with someone Males Very few car owners Incomes $50,000 - $60,000; not $75,000 and over More recreation trips Company D Live alone More car owners Company E Ages 24 and under and 55 and over; not 35 – 44 Post-graduate education More other shopping trips Company F Age 35 – 44 Few car owners Bachelor’s degrees Incomes $60,000 to $75,000 Note: Companies are not identified by name for proprietary reasons. Previous Research Findings Previous research suggests that factors such as age, income, education, and auto ownership may significantly influence the market segments which are receptive to car-sharing. A meta-analysis of the previous studies is presented in Exhibit 3-3, followed by discussions of individual factors.

Car-Sharing: Where and How It Succeeds Page 3-9 Exhibit 3-3 Literature’s General Consensus Regarding Typical Characteristics of Car-Sharing Members Characteristics Typical Car-Sharing Member Age Mid 30s to mid 40s Income Upper middle class (but real variations here) Education Upper levels (college degree(s)) Household size Smaller than average (1 – 2 persons) Auto ownership Half own one vehicle Gender Slightly more attractive to males Age Analysts seem to agree that car-sharing is attractive to a relatively narrow age range: • Average ages of US car-sharing members are in the mid-30s (Brook, 2004). • The 24 to 44 age bracket is overrepresented among Cooperative Auto Network members in Vancouver, BC (Jensen, 2001). • Most members of Communauto, Quebec, are in the 30 to 49 age bracket (Robert, 2000). • PhillyCarShare members are mostly in the late 20s and 30s (Lane, 2004). • Members of car-sharing programs are typically identified as young families (30 to 50 years old) (Hope, 2001). • The typical car-sharer in Germany as well as in the Netherlands is of a medium age (31 to 40 years) (Harms & Truffer, 1998). • Car-sharing members in Germany, Norway, Switzerland, and Swe- den are described as being middle aged (Klintman, 1998). • Average age of car-sharing members in Gothenburg, Sweden is between the ages of 29 and 49 (Polk, 2000). Education High levels of education are the norm: • “[High] Education levels seem to be the strongest predictor of whether someone becomes an early adopter” (Lane, 2004). • US car-sharing members are highly educated and most have a col- lege degree (Brook, 1999, 2004). • High education is a hallmark of Austrian members (Steininger, Vogl & Zettl, 1996).

Chapter 3 • Market analysis September 2005 Page 3-10 • The typical car-sharer in Germany as well as in the Netherlands is well educated (Harms & Truffer, 1998). • The average member of the Majornas Car Cooperative in Gothen- burg, Sweden, is a university- or college-educated male or female (Polk, 2000). • Car-sharing members in Germany, Norway, Switzerland, and Swe- den are described having a higher than average formal education (Klintman, 1998). Income Median or higher than average incomes are the norm: • Income is variable but 31% are in the highest bracket (over $40,000 Canadian) (Robert, 2000). • Incomes are near the median for all US car-sharing organizations (Brook, 2004). • There are higher than average incomes in Gothenburg, Sweden (Polk, 2000). • In Germany, 20% belong to a low-income group; 18% belong to a very high-income group (Harms & Truffer, 1998). Gender Previous literature indicates that, contrary to our survey, car-sharing is more attractive to men: • Car-sharing members are evenly divided as to gender (Brook, 2004). • Car-sharing members in Germany, Norway, Switzerland, and Swe- den are predominantly male (Klintman, 1998). • Car-sharing members show a predominance of well-educated men in Norway (Berge, 1999). Household characteristics There are some substantial disagreements in the previous literature concern- ing household characteristics: • Members are evenly divided as to marital status and home owner- ship (Brook, 2004). • Members are typified as young families (Hope, 2001). • The typical car-sharer in Germany lives in a small household (one to two persons) (Harms & Truffer, 1998). • Most members live in a rental apartment with a partner and/or child (Polk, 2000).

Car-Sharing: Where and How It Succeeds Page 3-11 Review of the Literature The consensus of the previous literature is that the typical car-sharing member is likely to be: • Well-educated (college or post-graduate degree) • Possessing a higher than average income • Between the ages of 25 and 45 • From a small household Our survey supports all of these conclusions. The literature also suggests that the typical car-sharing member is slightly more likely to be male, which was not supported by our survey. Behavioral Characteristics The internet survey of car-sharing members provided some information about the behavioral characteristics of car-sharing participants. Behav- ioral information was gathered about trip purpose, auto ownership, trip frequency, expenses, miles driven, and alternatives to car-sharing. Trip Purpose Respondents were asked to report all the different purposes of trips made using car-sharing, the major purpose of the last trip they made using car- sharing, and trip frequencies. The second question allows some estimates to be made of the relative importance of each trip purpose. Responses were relatively evenly distributed and are shown in Exhibit 3-4. Canadian members were more likely to use car-sharing for recreational trips than their US counterparts.

Chapter 3 • Market analysis September 2005 Page 3-12 Exhibit 3-4 Car-Sharing Trip Purpose Purpose % Using Car-Sharing for This Purpose Trip Frequency (Trips per Month)**On Any Trip* On Last Trip Recreation / social 55.4% 16.0% 1.7 Other shopping 50.9% 16.8% 1.3 Grocery shopping 49.4% 16.2% 1.7 Personal business 44.5% 24.7% 1.6 Work-related 21.2% 12.2% 2.2 Unspecified / other*** 9.5% 11.9% 2.2 To and from work 5.5% 2.1% 3.1 * Multiple responses permitted; therefore, percentages add up to more than 100%. **Frequencies only apply when trips were actually made for that purpose (i.e., zero values are not included). This is particularly important related to trips to and from work, since only 5.5% of respondents made trips in this category. ***Other trips included transporting family and friends (2.5%), moving furniture or hauling large loads (1.7%), medical appointments (1.1%), and visiting relatives (1.0%). Reasons for using car-sharing for particular trips also illuminate important market segmentation information. Respondents to the car-sharing survey reported that their main reasons for using car-sharing for this last trip (up to three responses permitted, so percentages add up to more than 100%) were: • Had things to carry 47.8% • Needed a car to get to their destination 37.8% • Had multiple stops to make 25.8% • Cost was acceptable for this trip 24.0% • Too far to walk 17.9% • More comfortable than other options 16.7% • Cost was better than for other travel options 16.0% • Ease of drop-off [no parking hassles or cost] 14.0% • Didn’t want to use public transit 13.2% Other reasons for using car-sharing for this trip included: • Arranging and picking up a rental car would have taken too long • Can’t get there except by car • Car-sharing was faster and/or more flexible than the other options • I had to go multiple places in a short time • Public transportation was not available for this trip • Public transportation would have taken too long

Car-Sharing: Where and How It Succeeds Page 3-13 Some gender differences were apparent in responses to this question. Men more often cited cost and not wanting to use other modes as motivating fac- tors for using car-sharing for the last trip. Women more often cited having multiple stops and needing a car for that particular destination. The youngest car-sharing members (24 or under) more often cited an ac- ceptable cost for this trip, greater comfort than other options, and having things to carry as reasons for using car-sharing than other age groups, and less often cited having multiple stops. The 45 to 54 year olds more often than others cited having multiple stops and carrying passengers. Individuals of different income levels cited different reasons for using car- sharing for the last trip, as follows: • Incomes between $10,000 and $20,000 per year (4% of the sample): More often cited having passengers, greater comfort than other options, and other reasons, and less often cited not wanting to travel by taxi. • Incomes between $20,000 and $30,000 per year (7.7% of the sample): More often cited an acceptable cost for this trip, hav- ing things to carry and not wanting to use public transit, and less often cited needing a car for that destination. • Incomes between $30,000 and $40,000 per year (11.3% of the sample): More often cited an acceptable cost for this trip. • Incomes over $75,000 per year (35% of the sample): More often cited needing a car for that destination and better cost than other options. • Incomes over $125,000 per year (10% of the sample): Were less often concerned about having things to carry. Respondents felt that car-sharing partly replaced other modes and allowed them to make trips that they would not be able to make otherwise. If car- sharing had not been available for this particular trip, 29.3% of the respon- dents would not have made the trip. Another 20% would have used public transportation; 12.6% would have used a rental car; 10.5% would have gone by taxi; and 9.3% would have borrowed someone else’s car. Some of the other respondents would have postponed or rescheduled the trip for when a vehicle was available or would have made multiple trips by walking or other modes. Those who lived in households with cars would have used their own car for this trip or would have ridden with someone else. Persons with the least education (high school diploma or less) and lowest incomes ($20,000 or less) would not have made the trip, suggesting that car-sharing

Chapter 3 • Market analysis September 2005 Page 3-14 is improving mobility most for low-income households. Men and persons with the highest incomes would be more likely than others to take a taxi. Having access to an automobile was seen as a distinct advantage by many car-sharing members. They were asked “For which of your trips do you feel that you really need to travel by car (including a personal vehicle, car- sharing, or a rental car)?” The most frequent responses (multiple responses permitted, so percentages add up to more than 100%) were: • Recreation / social trips 65.3% • Other shopping 44.9% • Grocery shopping 42.1% • Personal business 36.0% • Work-related trips (e.g., meeting clients) 19.4% • Other kinds of trips 11.4% The other kinds of trips for which a car was deemed necessary mirrored the answers above concerning trip purposes: transporting family and friends, moving furniture or hauling large loads, medical appointments, and visit- ing relatives. Auto Ownership Nearly 28% of all respondents to the survey lived in a household with an owned vehicle. Excluding no-car households, the average number of ve- hicles owned was 1.35. In 81.2% of the households with cars, the car-sharing member was, at least some of the time, a driver of that car (or those cars). The features of car ownership that were liked most included instant access at any time of the day or night (76.4%) and a variety of other benefits (10.8%). Chief among these other benefits was the ability to travel long distances at an affordable rate and customizing the car’s use to one’s own preferences (keeping child seats in the car, carrying animals, smoking in the car). Hav- ing a vehicle of their own choice and being sure that the car is well cared for were important to only 3% and 2% of the respondents, respectively. Five percent of the respondents reported that they don’t like anything about owning a car. The most disliked features of owning a car are shown in Ex- hibit 3-5, and relate largely to costs and hassles.

Car-Sharing: Where and How It Succeeds Page 3-15 Exhibit 3-5 Most Disliked Features of Car Ownership Feature Percent Respondents Cost of insurance and upkeep 38.3% Hassle of owning a car 28.8% High purchase costs of cars 15.9% Parking hassles and costs 9.2% Other factors* 5.2% * Negative environmental consequences and social costs were a large portion of these other factors. Trip Frequency Respondents reported making an average of 3.34 trips per month using car- sharing. The median number of trips per month was two. US members were overrepresented in the lowest trip frequencies (less than three per month); Canadian members were overrepresented in all trip frequencies greater than three per month, but especially those trip frequencies of more than six per month. The number of trips per month varies considerably depending on the trip purpose, as shown in Exhibit 3-4. Monthly Expenses Respondents reported paying, on average, slightly more than $60 per month for their use of car-sharing services. Mileage Driven Respondents reported driving, on average, about 3,850 miles per year at the current time. This figure applies both to shared vehicles and vehicles owned by household members. This is approximately 63% of the mileage that they previously drove, which is a substantial reduction in driving. Alternatives to Car-Sharing If car-sharing services stopped, the current car-sharing members reported that they would: • Use transit more often 38.6% • Get rides from friends 35.7% • Use taxis more often 33.9% • Buy a car 30.5% • Walk more often 14.8% • Other responses 23.1%

Chapter 3 • Market analysis September 2005 Page 3-16 Multiple responses were permitted, so these percentages add up to more than 100%. Among the hundreds of other (open-ended) responses to this question, the most frequent by far was to rent cars more often (8.2% of all respondents). A surprising number of respondents provided answers that were somewhat exaggerated but imply a sense of loss (be sad, cry a lot, “Die a horrible, painful death,” move out of the US, shoot myself, sink into despair, suf- fer). A few suggested that they would “do anything I could to start it up again.” A number of people would borrow cars more often, use their cars more often, or not make specific trips. A few thought that there would be no impact on them. Attitudinal Characteristics Car-sharing members are thought to hold strong views about a variety of environmental and social concerns. Respondents to the internet survey were asked a number of questions about such concerns, and their responses generally confirmed the anticipated strength and depth of their feelings: • Social activists: Almost half of the 1,340 respondents (48.3%) strongly agreed with the statement that “It’s my responsibility to help create a better world.” Another 41.5% agreed with this state- ment, creating an overall 89.8% who agreed or strongly agreed. The social activists tend not to be members of any specific demo- graphic subgroup. • Environmental protectors: Respondents to this survey of car- sharing members were at least as strongly concerned about envi- ronmental issues, if not more concerned, than car-sharing respon- dents in other studies. When asked about the statement, “I am very concerned about environmental issues,” 47.8% said that they agreed and another 39.3% said that they strongly agreed, for an overall total of 87.7% in agreement with this statement. Environ- mental concerns were also voiced in a large number of responses to other questions. The environmental protectors are more likely to be among the oldest car-sharing members (in terms of age, not length of membership) and are slightly more likely to be living with someone else. • Innovators: Car-sharing members are thought to be innovators and experimenters. This was confirmed in their responses to the statement “I like to try out new ideas”: 30.9% strongly agreed and 55% agreed, for an overall 85.9% agreement. The innovators were more likely to be in the lowest income group and to be under 34.

Car-Sharing: Where and How It Succeeds Page 3-17 • Economizers: Car-sharing members are also thought to be cost- sensitive. This preconception was borne out in their responses to the statement, “Saving money is very important to me” – 31.6% strongly agreed and 50.7% agreed with this, for an overall 82.3% agreement. Economizers are most definitely not auto owners; this relationship is very strong. Car-sharing members (at least the economizers) appear to be much more aware of the costs of auto- motive travel than are auto owners in general. Economizers also tended to be under age 34 and in the lowest income group. • Not car status consumers: On the other hand, very few car-shar- ing members derive a strong sense of status from their vehicles. With respect to the statement, “The car I drive is an important reflection of my personality,” only 2.3% strongly agreed and an- other 14.7% agreed, leading to an overall agreement of only 17%, the lowest of the attitudinal factors measured. Persons who were more likely to agree that their car did reflect their personality were much more likely to own a car. They also tended to have incomes greater than $75,000 per year, and to be between the ages of 25 and 44. Motivations for Joining Car-Sharing Asking why people join car-sharing helps to identify groups of customers who can be targeted by specific messages. This approach is “based on the belief that the benefits that people seek in consuming a given product are the basic reasons for the existence of true market segments… When properly executed, this approach is widely acknowledged as one of the best ways to segment markets” (Elmore-Yalch, 1998). Web-Based Survey The internet survey conducted for this project offered respondents the op- portunity to identify many motivating factors for joining and using car-shar- ing. According to the respondents, their reasons for joining car-sharing were that: • They liked the car-sharing philosophy: 81.2% • They could eliminate the hassles of owning a car 64.6% • They liked having another mobility option 54.1% • They wanted to spend less on transportation 35.5% • Car-sharing services came to their neighborhood 35.2% • They couldn’t afford to own/maintain/garage a car 31.8% • They were aware that car-sharing was now available 31.6% Multiple responses were permitted, so these percentages add up to more than 100%.

Chapter 3 • Market analysis September 2005 Page 3-18 Some of the more interesting “Other” reasons, cited in 13% of the responses, included: • “As a musician, I needed a way to get to gigs that was flexible, convenient, and inexpensive.” • “Birth of a son . . . nice to be able to get places by car occasionally with him in tow.” • “Costs beat renting for a day!” • “Friendlier for the environment.” • “Had my car stolen 3 times. Decided to sell it.” • “I don’t own a car and don’t want to, but sometimes I need one.” • “I want to support this kind of energy efficient, environmentally friendly effort.” • “Liked having freedom (not asking friends for rides).” • “Live in a rural ecovillage that does not allow personal cars.” • “Reduced us from 3 cars to 1 car plus car-sharing.” • “Wife left me, took car.” Among all the reasons cited, the primary reason for joining was: • Eliminated the hassles of owning a car 21.8% • Liked the car-sharing philosophy 19.1% • Liked having another mobility option 15.5% • Couldn’t afford to own/garage/maintain my car 14.5% • Other reason 29.1% For those who already own cars, they were much more likely to join car- sharing if their employer paid the cost, if their car broke down, or if they liked the overall philosophy. Men were more likely than women to say they joined because they just found out about it or they liked the philosophy; women were more often responsive than men to having their employer pay the cost. People who lived with someone were more likely than those who lived alone to be motivated by employer payments and a car that just broke down. Canadians were overrepresented among the following primary reasons for joining car-sharing: wanted to spend less on transportation, just found out about it, couldn’t afford to own / maintain / garage my car, and car broke down or needed extensive repairs. US members were overrepresented in these reasons: my employer pays for membership or other expenses, and car-sharing services came to my neighborhood.

Car-Sharing: Where and How It Succeeds Page 3-19 Cost savings are the most attractive feature of car-sharing, according to re- spondents (Exhibit 3-6). Environmental and ease-of-use features were also cited by most respondents, but were not the primary attraction. The least attractive features of car-sharing are considered to be costs and, to a lesser extent, the need to make reservations (Exhibit 3-7). The apparent contradiction, with costs considered both the most and least attractive feature of car-sharing, may be explained as the results of different perceptions. Car-sharing may appear cheap to people who have never owned a car, but expensive to those who have owned one for many years. Exhibit 3-6 Most Attractive Features of Car-Sharing Feature % Citing This Feature* % Citing As Most Attractive Feature Less costly than owning a car 85.3% 31.9% The overall philosophy of car-sharing 78.9% 16.4% Helps the environment 77.0% 10.2% Less hassle than owning a car 74.9% 16.7% Can pay for a car only when using a car 74.6% 12.2% Easy to use 60.3% 1.8% Easy to make reservations 57.9% 0.5% Don’t have to ask for rides from others 49.5% 5.2% No parking hassles 41.7% 1.7% Reliability – cars are there when I need them 35.9% 2.0% Other 4.3% 1.5% * Multiple responses permitted; therefore, percentages add up to more than 100%.

Chapter 3 • Market analysis September 2005 Page 3-20 Exhibit 3-7 Least Attractive Features of Car-Sharing Feature % Citing This Feature* % Citing As Least Attractive Feature Hourly costs are too high 33.9% 20.2% Mileage costs are too high 26.2% 10.6% Hard to extend the rental time 24.1% 7.7% Have to reserve a vehicle too far in advance 22.1% 7.1% Hard to get vehicles at the times I need them 21.3% 8.8% Distance/effort to get to the vehicle 19.6% 7.1% Hard to get a vehicle when I need it 17.2% 5.5% Vehicles not available close to me 15.9% 6.1% Vehicles not always clean 13.3% 3.2% Membership costs are too high 9.3% 3.0% Billing procedures 7.0% 2.3% Vehicles are in inconvenient / unsafe locations 5.8% 1.2% Vehicles not always in good working order 5.5% 1.2% Vehicles not attractive or not the right size 4.7% 1.4% Hard to get information or reservations 3.4% 0.7% Other 16.7% 13.8% * Multiple responses permitted; therefore, percentages add up to more than 100%. Some very specific complaints (which may not apply in all situations) included: • “All trips must be round trips; have to pay for time when car is idle.” • “Bad for visiting and browsing (when hours are long).” • “Can’t be spontaneous – may not be able to get a car.” • “Difficult to judge how long to reserve the car – I often use it less than the time reserved.” • “Feel under time pressure while doing errands with a shared car.” • “Hard to extend rental time because I don’t have a cell phone.” • “Hard to give up a reservation and not get billed for the time.” • “Must drop the car off where I picked it up.” • “No guarantee that a car will be there when I need it.” • “Some car share members do not respect the cars.” • “The phone system misunderstands me.” • “Too expensive for a long trip or a long stay at your destination.”

Car-Sharing: Where and How It Succeeds Page 3-21 Focus Groups Participants in focus groups held in Boston, San Francisco, and Washing- ton, DC had similar perspectives on what they considered to be motivating factors for joining car-sharing. Focus group participants reported that the most persuasive motivators for them were that car-sharing: • Provided a philosophy that strongly resonated with them • Offered them another “mobility option” • Eliminated the hassles of owning a car • Reduced their transportation costs • Became attractive after they moved into a neighborhood where it was available • Fills a “mobility gap” for big purchase trips as well as for places and times of day that are not served by transit Some of the specific comments about motivations for using car-sharing were: • “It offers the use (and cost) of a vehicle for only those hours needed.” • “It is more attractive when closely integrated with public transit services.” • “I feel liberated by not having a car – liberation means a combina- tion of having more money and more choices of what to do with that money – and no hassles.” • “I know that sometimes I will need to use a car but car-sharing makes more sense to me in terms of the energy and the environ- ment [than owning a car].” • “It seemed like a great idea and I started to feel almost a sense of pride watching it grow. I guess I could identify with the people starting it and wanted to encourage the effort.” Previous Research Previous analysts have offered the following observations concerning moti- vations for joining car-sharing. In general, these support the findings from the web-based survey that there are multiple reasons for joining, including economic, environmental and convenience factors: • According to Lane (2004), convenience was the most important reason cited for joining (41%), followed by affordability (20%), personal freedom (16%), environmental friendliness (10%), fewer hassles (6%) and improved productivity (2%). Lower-income members were more likely to cite affordability and personal free- dom – higher-income ones were more likely to cite convenience.

Chapter 3 • Market analysis September 2005 Page 3-22 • Steininger, Vogl & Zettl (1996) found that motivations of Austrian members for joining (in priority order) were: o Their own contribution to traffic mitigation o Lower car use due to environmental concerns o The desire to have a car available at good value for money o An interest in seeing fewer cars produced o Not being required to produce the effort to care and maintain the car o A desire to drive newer cars which are less polluting • According to Harms & Truffer (1998), motivations for joining car-share services have changed over time. In Switzerland, early adopters were ecologically motivated, and the organization had a social value as most members knew one another. Although environmental consciousness is still important, it lost ground to financial and pragmatic motivations as the program grew. • Polk (2000) found that, in a study in Sweden, economic and practi- cal reasons were the most important reasons for joining, with environmental, cooperative ideology less important, and social (opportunity to meet others) not important at all. • Based on a study in Seattle and Berlin, Schwieger (2004) suggests that US members are more rational about their decision to join car-sharing, while the German members were drawn by emotional reasoning. • A survey of Cooperative Auto Network members in Vancouver, BC highlighted a mix of environmental, economic and practical concerns, as shown in Exhibit 3-8 (Jensen, 2001). Exhibit 3-8 Reasons for Car-Sharing Membership: Cooperative Auto Network (CAN) Members Reasons Very Important Important Total CAN is less expensive than leasing or buying a vehicle 65% 30% 95% I’m concerned about the environment 53% 39% 92% Convenience – I don’t have to spend time or money on maintenance 50% 40% 90% I like the cooperative structure of CAN 20% 55% 75% I wanted access to a variety of vehicles 8% 36% 44% I wanted access to a second car 4% 6% 10% Source: Jensen (2001)

Car-Sharing: Where and How It Succeeds Page 3-23 Some other reasons that appeared on the CAN survey included: • Wanting to support the idea of car-sharing and collective owner- ship • Not wanting to own a car • Enjoying the reliability of well-maintained and new cars • Promoting a non-consumer lifestyle • Maintaining driving experience • Less stressful than owning a vehicle One recent avenue of research has focused on the “trigger points” that are thought to be important for joining. For example, Brook (2004, p. 4) sug- gests: Member surveys repeatedly indicate that very few people actually sell a vehicle and join a carsharing organization when they first hear about carsharing. In most cases, it appears that people continue their existing transportation patterns, whether they own a vehicle or rely on public transportation, walking or bicycle, until some event in their lives prompts them to consider alternatives. This “trigger event” may be a change of jobs, marital status, moving to a new home (particularly if it’s in a new city), etc. For car owners it may be the prospect of major out of pocket costs to repair an older vehicle, failure to pass a required smog test or a major accident. This hypothesis has been tested with extensive qualitative research in con- tinental Europe. In particular, Harms (2003) concludes that car owners have to experience a disruption in their routine behavior before they consider car-sharing. These disruptions might be changes in a person’s life situation, or to mobility requirements, opportunities or abilities (for example, the breakdown of a household car). In turn, the disruption of routines fosters a more conscious, rational decision-making state, which is more favorable to the adoption of car-sharing. In Britain, meanwhile, a study of rural car-shar- ing found that 77% of joiners had experienced one of these trigger events, such as moving (25%), selling a car (19%) or changing job (14%) (Carplus, cited in Cairns et al., 2004). A general consensus of the previous studies suggests that primary motiva- tions for joining a car-sharing organization will include the characteristics shown in Exhibit 3-9.

Chapter 3 • Market analysis September 2005 Page 3-24 Exhibit 3-9 General Literature Consensus Regarding Motivations of Typical Car-Sharing Members Motivations Relative Importance Desire to save money High to very high Concern about environmental issues High to very high Convenience – not dealing with maintenance, etc High to very high Changes in one’s personal life situation Moderate to high Positive attributes of the car-sharing experience Moderate Work-related conditions Moderate to low Of these motivations, some of the best predictors of car-sharing membership are said to be the desire to save money, concern about environmental issues, and the convenience of not owning a car (or another car). reasons for terminating Car-Sharing Memberships For this project, a focus group was conducted with individuals who were no longer active car-sharing members. Members of this group were surpris- ingly enthusiastic about car-sharing and said that they would definitely use it again. “I certainly enjoyed the service while I had it. It was great to have that as an option.” Most participants had not actively used car-sharing in 12 months or more, but they kept their membership as a “just in case” kind of insurance: “if something happened to my car, having car-sharing would be fabulous.” These focus group participants could be called “pragmatists” in that they had used car-sharing when the specific details of the economics and trip logistics made sense to them and had used other modes when they made the most sense. These individuals had stopped using car-sharing because of a significant life change: • Most of these individuals had purchased a vehicle, and this pur- chase was currently providing most of the transportation that they needed. • Several individuals had moved their residence to a location less conducive to car-sharing. • Marital status changes (often in conjunction with the above rea- sons) accounted for the next most frequent reasons for no longer using car-sharing. There is very little published data on the reasons for terminating car-sharing memberships. One of the few exceptions is AutoShare in Toronto, which has

Car-Sharing: Where and How It Succeeds Page 3-25 reported about a 20% customer-turnover in its first five years. Reasons for leaving included the following (data from www.autoshare.com): • 26% moved out of Toronto • 20% acquired a car (e.g. through marriage, inheritance, etc.) • 17% reported miscellaneous reasons (not related to service quality/cost) • 15% reported that their lifestyle has become completely car-free • 12% had to buy a car for a new job • 10% felt that AutoShare was too expensive • 3% reported that “AutoShare didn’t work for me” • 2% were inconsiderate and were asked to leave Multiple responses were permitted, so these percentages add up to more than 100%. Summary of Demographic Market Segments attracted to Car-Sharing From the results of the internet survey of members of car-sharing orga- nizations, the focus groups with persons using car-sharing, and previous literature about individuals likely to be attracted to car-sharing, a general consensus appears to be that car-sharing currently appeals to persons who are: • Residents of dense urban areas • Highly concerned about environmental and social issues • Highly educated • Middle to upper income, but still cost-sensitive • Not high-mileage drivers • Considered to be innovators • From smaller households (two persons or less) • More concerned with what a vehicle can be used for, less con- cerned with how it looks or its brand name attributes • Generally in their 30s or 40s (although this can vary greatly by specific location and other service attributes)

Chapter 3 • Market analysis September 2005 Page 3-26 3.2 Geographic Markets Car-sharing is overwhelmingly concentrated in the cores of the largest metropolitan regions. In the United States in 2003, 94% of membership was concentrated in eight metropolitan regions – San Francisco, Los Angeles, San Diego, Portland, Seattle, Boston, New York, and Washington, DC (Shaheen, Schwartz & Wipyewski, 2004). The same picture, although to a lesser extent, is true in Canada and in Europe. While car-sharing operates in some smaller communities such as Aspen, CO, in others such as Halifax, Nova Scotia the organization has been forced to close down. In Traverse City, MI, the 20-member formal car-sharing program ended in June 2002 after two and a half years, primarily because sufficient volunteer labor could no longer be found, and the program was not large enough to support paid staff. Note that in this section, the following terms are used: • Pod – a location with one or more car-sharing vehicles • Pod neighborhood (or pod area) – the area within 1/2 mile of a car- sharing pod Current Market Settings A range of studies have identified several common neighborhood characteris- tics necessary for car-sharing to succeed (Muheim & Partner, 1998; Klintman, 1998; Brook, 1999, 2004; Bonsall, 2002; Meaton, 2003). These include: • Parking pressures. Car ownership is more expensive and less con- venient in places where parking is scarce, making car-sharing a relatively more attractive option. If residents have to walk a block or two to their car, they may as well walk the same distance to a car-sharing location. • Ability to live without a car. Car-sharing is not designed to meet a household’s entire mobility needs, but to work in concert with other modes such as transit (see Chapter 2). The availability of good public transportation is therefore key, along with local shop- ping opportunities and a pedestrian and bicycle network. • High density. Density has two major impacts on the viability of car-sharing. Firstly, it means that there is a larger customer base within walking distance of each car-sharing vehicle; doubling the density will double the number of potential customers for a given vehicle. Secondly, it means that these potential customers will have a higher propensity to join, since dense neighborhoods have lower rates of vehicle ownership and travel (Exhibit 3-10). This is partly due to the effects of density itself, since the higher the den-

Car-Sharing: Where and How It Succeeds Page 3-27 sity, the greater the number of nearby destinations and the shorter the trips; and partly because density correlates strongly with other factors, such as the availability of local shopping, parking costs and the pedestrian environment. • Mix of uses. Business members have been shown to have an important role in increasing utilization rates and evening out the demand cycle, since they tend to use the cars during the working day. In contrast, people using car-sharing for personal trips have a peak demand in the evenings and at weekends. The potential for this pairing of user groups with different demand patterns is greatest in mixed-use neighborhoods, where car-sharing can at- tract both business and individual members. Exhibit 3-10 Density vs. Household Vehicle Ownership Source: Holtzclaw et al. (2002). A similar curve is found when plotting density against vehicle travel (vehicle miles traveled per capita) These factors are highly intercorrelated. Parking, for example, tends to be scarce in dense, mixed-use neighborhoods with good transit, while density is one of the most important factors determining the viability of high-fre- quency, high-speed transit. Other Market Settings These types of urban neighborhoods – dense, mixed-use with scarce parking and good transit – appear to offer the best potential for car-sharing. However, there are also other types of market setting where car-sharing has been in- troduced and appears to be viable. Three types are discussed in this section: university campuses; apartment buildings; and small towns and villages. San Francisco Los Angeles Chicago

Chapter 3 • Market analysis September 2005 Page 3-28 Several potential future markets have also been suggested, such as national parks, military bases and other settings where land use and transportation decisions are controlled by a single entity. University Campuses University campuses have been one of the most fertile environments for car-sharing. They tend to have constrained parking and a highly educated community with many “early adopters” who have a desire to reduce their impact on the environment. Many campuses have requirements that parking and transportation services be self-funding through parking fees and fines and other user charges, which means that they are more likely to need to explore aggressive Transportation Demand Management (TDM) programs, including car-sharing (see, for example, Toor & Havlick, 2004). Many campuses are situated in urban centers and can be considered part of the “core” urban market for car-sharing – even though they may have devel- oped partnership arrangements with a car-sharing operator (see Chapter 5). For example, Massachusetts Institute of Technology in Boston, the University of California-San Francisco, and the University of Washington-Seattle are all located in urban centers that share the basic characteristics for car-sharing viability – good public transportation, high density, mixed uses and park- ing scarcity. In many cases, vehicles are likely to serve users from both the campus itself and surrounding neighborhoods. In other cases, however, campus car-sharing operates in more geographically isolated contexts, outside of the urban core. Examples include: • Stanford University, CA • Princeton University, NJ • University of North Carolina-Chapel Hill In addition, several other campuses, while located in major metropolitan areas, are geographically separated from surrounding high-density neigh- borhoods. Examples include the University of California-Los Angeles and the University of British Columbia-Vancouver. Apartment Buildings Developers in many cities have sought to partner with car-sharing organi- zations, for a variety of reasons including parking management and pro- viding an amenity to tenants (Chapter 5). In most cases, the cars are part of the operator’s regular network and function as part of the core network.

Car-Sharing: Where and How It Succeeds Page 3-29 For example, Zipcar has a vehicle at the Market Commons development in Clarendon, VA, which is located on-street (albeit on a private road), and accessible to all members. City CarShare’s vehicle in the 8th and Howard apartments in San Francisco is located in the apartment building’s garage, but is open to all members. Other vehicle locations, however, rely on members drawn from the apart- ment building itself, and are closed to other members. This means that the neighborhood characteristics are less important – although factors such as public transportation still play an important role. For example, many of Viacar’s vehicles in Detroit apartment complexes are available for the buildings’ tenants only. Small Towns and Villages While urban areas may offer greater potential, car-sharing programs have also been introduced in smaller cities and more rural areas. Examples include British Columbia, where the Cooperative Auto Network has vehicles in small towns in the Vancouver region, and Rutledge, MO, where the Dancing Rab- bit Vehicle Cooperative is part of an “ecovillage” development. Europe provides even more examples: Switzerland, Austria, Germany and the Netherlands all have car-sharing programs in rural areas. In Austria, for example, villages with a population as low as 1,000 people are served (Koch, 2002); in Sweden rural car-sharing cooperatives serve towns of a similar size, such as Färnebo. In the UK, the UK Countryside Agency has funded pilot projects in 13 areas (see, for example, CarPlus, 2004; The Countryside Agency, 2004). Car-sharing has also been established in many small cities, such as Aspen, CO and Kitchener, ON. While these operate at a different scale compared to major metropolitan operations, they share many of the same characteristics such as the availability of good public transportation and local services. Small-town and village car-sharing appears to be characterized by a high degree of personal involvement by the members. In some cases, this is pro- vided by volunteers, such as at the Dancing Rabbit ecovillage, or in Traverse City, MI where the withdrawal of the volunteers led the program to close. According to studies in Britain, the presence of a strong local champion is more important in making rural car-sharing feasible than factors such as good public transportation (Meaton, 2003).

Chapter 3 • Market analysis September 2005 Page 3-30 Other programs, however, have had success through sharing administration with a “parent” car-sharing organization. The Cooperative Auto Network has five rural locations in Tofino, Nanaimo, Courtenay, Cortez and Whistler, operated through its Vancouver headquarters. It will place cars anywhere that 16 “committed pioneers” are willing to both purchase shares in the co- operative, and actively pursue other members. A similar approach is used by Mobility Switzerland. It will open a new location where 20 members are already signed up, and where at least five new customers can be recruited during the first year. Other criteria include the availability of reasonably priced parking, proximity to transit, and good lighting for personal security (Mobility Switzerland, 2004). analysis of existing locations The studies discussed in the previous section were largely qualitative in nature, assessing the broad characteristics of neighborhoods with car-shar- ing. This section provides more quantitative data on the market settings for car-sharing, through an analysis of census data. These detailed neighborhood characteristics are critical to the success of car-sharing, not least since the distance of a car-sharing pod from members’ homes is strongly correlated both with the propensity to use car-sharing (Katzev, Brook & Nice, 2000), and with member satisfaction. This satisfaction related to distance from a pod covers not only convenience, but surprisingly also reliability, car avail- ability, ease of use and cleanliness (Lane, 2004). Use of Census Data: An Example from Madison Census data have been used by many operators in determining where to locate new pods, and the feasibility of starting service in a particular city. For example, in Madison, WI the car-sharing feasibility study used this source to determine which neighborhoods to take forward for a market study (Grossberg & Newenhouse, 2002). The researchers analyzed four variables, selected based on a literature review, for each census tract within the city limits: • Percentage of workers commuting by non-auto modes • Average vehicles per household • Residential density • Percentage of population aged 16-24 The initial screening was undertaken using the commute mode split vari- able, and 12 tracts with the lowest auto mode splits taken forward. These

Car-Sharing: Where and How It Succeeds Page 3-31 12 tracts also had low vehicle ownership rates. Three tracts were eliminated at the next stage, because they were located near the university campus and more than 50% of residents were aged 16-24 and would not be eligible for the service (Community Car requires at least five years driving experience). While two of the remaining tracts were low density on average, they were retained since they incorporated high density areas. This example shows how census data can play an important role in deter- mining the feasibility of car-sharing in different settings. However, it raises several questions, particularly regarding the choice of variables. Intuitively, commute mode split, vehicle ownership and density (which tend to be closely correlated) are likely to be strong indications of the fertility of the ground for car-sharing. However, car-sharing has been successfully established on several university campuses, raising doubts about the importance of age-related demographic variables. More importantly, there has been little quantitative research into the existence of any thresholds, and whether dif- ferent variables may play an explanatory role. Methodology This section documents the results of a GIS-based analysis of the mar- ket settings of car-sharing pods in various cities. Census data were analyzed for all 13 US cities that have significant car-sharing operations – Aspen, Boston, Chicago, Denver-Boulder, Los Angeles, Madison, New York, Philadelphia, Portland, San Diego, San Francisco, Seattle, and Washington DC. Programs with fewer than four vehicles (such as Ann Arbor) and those on university campuses outside metropolitan regions (e.g. Chapel Hill) were excluded from the analysis. Full technical details of the GIS-based analysis are found in Appendix B. In contrast to the Madison example discussed above, which used census tracts, a much finer grain of analysis was used for the GIS analysis – census block groups. In the City of Madison (population 208,000), for example, there are 153 block groups but just 63 tracts. Sixteen variables (see Exhibit 3-11) were analyzed at two different scales:1 • One-half mile radius from every pod – considered the typical dis- tance people are willing to walk to a pod • Regional averages, for comparison purposes (for all variables ex- cept intersection density and residential density) . For an initial analysis of six cities, data were analyzed for a ¼-mile radius and ½-mile radius, and results were found to be similar.

Chapter 3 • Market analysis September 2005 Page 3-32 The analysis looked at a range of census variables that may have an influence on the viability of car-sharing. These variables encompass demographics, commute mode share, vehicle ownership and neighborhood characteristics. Exhibit 3-11 compares the results for pod neighborhoods to the regional averages. This comparison helps identify the characteristics of pod neigh- borhoods that differ from other parts of the region. Exhibit 3-11 Summary of Demographic and Neighborhood Characteristics Pod Neighborhood Average Vehicles Weighted Evenly* Cities Weighted Evenly** Regional Average*** Difference 1 2 3 =1-3 Demographics % 1-person households 51.8% 51.0% 27.2% 24.6% % households with children 12.5% 12.5% 32.4% -19.9% % of rental households 71.5% 70.5% 39.6% 31.8% % households earning > $100,000 18.2% 16.7% 17.9% 0.3% % with Bachelor’s degree or higher 54.6% 52.4% 34.0% 20.6% Commute Mode Share % drive alone to work 33.0% 39.3% 69.4% -36.4% % carpool to work 6.6% 6.7% 11.6% -5.0% % take transit to work 30.8% 23.7% 8.8% 22.0% % bike to work 2.1% 3.1% 0.8% 1.3% % walk to work 21.9% 21.1% 4.4% 17.5% Vehicle Ownership % households with no vehicle 40.0% 34.7% 11.3% 28.7% % households with 0 or 1 vehicle 82.0% 76.9% 46.0% 36.0% Average vehicles per household 0.84 0.97 1.66 -0.83 Neighborhood Characteristics Housing units per acre 21.7 17.1 Intersections per acre 0.37 0.34 % units built before 1940 43.6% 34.9% 16.9% 26.7% * Mean of data for all individual vehicles, meaning that pods with more vehicles will be weighted more strongly. ** Mean of means for each city, i.e. each city is weighted the same regardless of car-sharing fleet size. *** Mean of means for each region. Household and Neighborhood Characteristics Almost without exception, pod neighborhoods in all 13 cities have distinctly different characteristics compared to their surrounding regions. Even the least dense pod neighborhoods with the lowest transit use still have higher

Car-Sharing: Where and How It Succeeds Page 3-33 densities and higher transit usage than the regional norm. Some of the main differences include: • Household Size and Composition and Education. One-person households are far more common in the areas surrounding pods. The presence of children is noticeably less likely as well. Residents living in pod-areas are also far more likely to rent and hold a Bachelor’s degree or higher. • Income. Surprisingly, income was not a noticeable factor in the resident profiles of pod neighborhoods in the 13 cities. On aver- age, pod-area residents’ income levels are within 1% of region- wide averages, but there are substantial variations from city to city. • Mode to Work. Residents in pod neighborhoods are far more likely to take transit and walk to work, rather than drive, com- pared to their regional counterparts. The high mode share for walking is also indicative of mixed-use development. • Vehicle Ownership. Residents of car-sharing neighborhoods own substantially fewer vehicles compared to the regional average, and are more likely to be car-free. • Neighborhood Characteristics. Car-sharing vehicles in most cities (Aspen, Chicago, Denver-Boulder, and Los Angeles are excep- tions) tend to be located in older, historic, neighborhoods, which are likely to be more walkable and have less off-street parking. Car-sharing neighborhoods also tend to have higher densities; in most cities, they fall into the range of 7 to 25 housing units per acre. Explaining Variations in Car-Sharing Service The previous section analyzed the fundamental characteristics of car-shar- ing neighborhoods. This section takes the analysis further, by analyzing the amount of car-sharing – the level of service – that different neighborhoods can support. The level of service concept is often used with other modes, such as automo- biles and transit. For this study, a “car-sharing level of service” indicator was defined to indicate the total amount of service – i.e., the number of car-shar- ing vehicles – in a given neighborhood. This allows analysis of the amount of service that can be supported by neighborhoods of different types. The car-sharing level of service was calculated for each pod based on the total number of vehicles within the half-mile radius. Exhibit 3-12 shows an example of how the level of service was calculated. In this example, the level of service for the pod located in the center of the circle is 10 because

Chapter 3 • Market analysis September 2005 Page 3-34 there are a total of 10 vehicles in various pods within the half-mile buffer. The variables were tested for the entire data set as a whole, and individu- ally for the eight cities with a medium-sized to large car-sharing operation (25 vehicles or more). Exhibit 3-12 Level of Service Calculation The results of the correlation analysis are shown in Exhibit 3-13. An asterisk indicates a strong relationship between the variables (statistically significant at the 5% level); two asterisks indicate a very strong relationship (statistically significant at the 1% level). For all the cities analyzed, level of service correlated negatively with drive alone to work and average vehicles per household – in other words, neigh- borhoods with lower drive-alone and vehicle ownership rates tend to have more car-sharing service. Level of service also correlated positively with households with no or one vehicle and households with no vehicle. Other variables with consistently statistically significant correlations (negative or positive) with car-sharing level of service include the percentages of one-person households, households with children, and rental households; commute mode share for walking and carpooling; intersection density; and residential density. Given that most variables have a high degree of correlation, it is interesting to look at which do not correlate – either for the data set as a whole, or for certain cities. These variables include transit commute mode share, which

September 2005 Page 3-35 Car-Sharing: Where and How It Succeeds Exhibit 3-13 Correlation with Car-Sharing Level of Service Pearson Correlation with Car-Sharing Level of Service Variable Boston Los Angeles New York Philadelphia Portland San Francisco Seattle Washington DC All Records % 1-person households .619(**) 0.124 .699(**) .679(**) .822(**) .236(*) .758(**) .441(**) .478(**) % households with children -.548(**) 0.106 -.593(**) -.627(**) -.729(**) -.552(**) -.646(**) -.303(**) -.412(**) % of rental households .198(**) 0.317 .230(*) .404(*) .760(**) .317(**) .653(**) .383(**) .301(**) % households earning > $100,000 .356(**) -0.15 0.148 0.145 -.308(**) 0.037 -.425(**) -.308(**) -.066(*) % with Bachelor’s degree or higher .210(**) -.483(**) .381(**) .573(**) -0.028 -0.055 -.472(**) -0.04 0.063 % drive alone to work -.441(**) -.620(**) -.406(**) -.627(**) -.851(**) -.480(**) -.758(**) -.653(**) -.431(**) % carpool to work -.503(**) 0.338 -.414(**) -.596(**) -.715(**) -.608(**) -.708(**) -.340(**) -.363(**) % take transit to work 0.033 .492(**) 0.043 -.626(**) .607(**) .477(**) .277(**) .198(**) .104(**) % bike to work -.149(*) -.425(*) .202(*) 0.109 0.005 -0.046 -.318(**) .688(**) -0.003 % walk to work .374(**) 0.337 .376(**) .718(**) .915(**) .281(*) .850(**) .538(**) .512(**) % households with no vehicle .427(**) .661(**) .551(**) .667(**) .902(**) .361(**) .832(**) .681(**) .399(**) % households with 0 or 1 vehicle .522(**) .485(**) .400(**) .735(**) .793(**) .422(**) .770(**) .633(**) .488(**) Average vehicles per household -.495(**) -.620(**) -.497(**) -.722(**) -.839(**) -.405(**) -.819(**) -.680(**) -.458(**) Housing units per acre .751(**) -.445(*) .379(**) .843(**) .636(**) .656(**) .671(**) .890(**) .174(**) Intersections per acre .374(**) 0.114 -.259(**) .577(**) .710(**) .475(**) .642(**) .519(**) .290(**) % units built before 1940 .311(**) -0.024 -.208(*) -0.26 0.144 .583(**) 0.142 .475(**) .223(**) * Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed).

Chapter 3 • Market analysis September 2005 Page 3-36 correlated positively in most cities but not in Boston, New York, and Phila- delphia. Income, education, bicycle commute mode share and the percentage of units built before 1940 were other variables that did not have a consistent correlation with car-sharing level of service. The correlation analysis shows that as level of service increases, so does the proportion of rental households, one-person households, households with low vehicle ownership, and transit and walking mode shares. Similarly, as level of service increases, the proportion of households with children, commuters who drive alone or carpool, and average vehicles per household decreases. Through multiple regression analysis, several models were tested for their ability to predict the level of car-sharing service for a neighborhood. It should be noted that New York appears as a case unto itself – it has very high residential density and very low vehicle ownership rates, and was therefore excluded from the regression analysis. For the other 12 cities, the best models were found to use vehicle ownership rates combined with walk mode share. This model predicts almost 50% of the variation in car-sharing between different neighborhoods. In other words, these characteristics of a neighborhood are half of the explanation for car-sharing success. Full details of the multiple-regression analysis are provided in Appendix B. The walking mode share variable suggests that car-sharing level of service is higher in areas that have a mix of residential and employment uses and areas that are more pedestrian friendly. Commute mode share for walk- ing has the strongest correlation with car-sharing level of service of any of the variables examined. The average vehicles per household variable has an intuitive connection to car-sharing success; in neighborhoods with lower vehicle ownership, more households are able to fulfill their daily needs without a car. While this formula provides a partial explanation of car-sharing success, there are clearly other factors that combine with these neighborhood characteristics to fully explain where car-sharing will succeed, such as the amount of capital that operators have to expand to the fullest market potential. Member Perceptions of Neighborhood Type Another source of quantitative data on market settings comes from the survey of car-sharing members. In addition to the information on demo- graphics (discussed earlier in this chapter) and social and environmental

Car-Sharing: Where and How It Succeeds Page 3-37 impacts (Chapter 4), various questions explored the types of neighborhood in which car-sharing members live. This enables issues such as parking availability to be explored, along with subjective impressions of the qual- ity of transit and the pedestrian environment – none of which are available through census data. Respondents to the internet survey furnished a good deal of information about the settings in which they lived. Most of them were center city resi- dents. They described their living environments as shown in Exhibit 3-14. As can be seen, these findings serve to confirm the results from the census data. Exhibit 3-14 Locational Information for Car-Sharing Members Locational descriptors Agree Strongly Agree My neighborhood has a good walking environment 46.2% 40.3% My neighborhood has good public transit service 48.5% 37.9% It’s easy for me to walk to a grocery store 37.2% 29.5% More than once, I have spent a long time looking for a parking spot in my neighborhood 26.3% 21.2% Nearly 60% of all respondents lived in a home that had a driveway, garage, or other off-street parking space, but nearly half of those persons (29% of total respondents) did not use that parking space. Of those who did use such a parking space, only 13% paid for its use. Combined with the fact that less than half of respondents report difficulties parking in their neighbor- hoods, this suggests that parking difficulties are just one of many factors influencing the success of car-sharing in a given neighborhood. Summary of results One of the main conclusions that can be drawn from this analysis is that car-sharing users are not necessarily representative of the neighborhoods surrounding car-sharing pods. For example, as discussed in the earlier part of this chapter, 83% of members surveyed have a Bachelor’s degree or some post-graduate work. In contrast, 55% of residents living close to pods have a Bachelor’s degree, higher than the regional average of 34% but still far below the 83%. Most importantly, although this variable has explanatory power in some cities, it is not consistently related to car-sharing success. In Portland, San Francisco and Washington, DC, there is little relationship

Chapter 3 • Market analysis September 2005 Page 3-38 between education levels in a neighborhood and the amount of car-sharing service. Another indication comes from income. As discussed in the earlier part of the chapter, there is a wide income spread among car-sharing members. The pod neighborhoods in Chicago, however, have some of the highest propor- tions of high-income households in any of the cities examined,2 even though the car-sharing program there has targeted low-income households. These differences between member and neighborhood characteristics are not unexpected, given that car-sharing’s member base consists of such a small proportion of residents. Instead, it seems that car-sharing is appealing to a large number of highly educated, but not necessarily high-income, gentrifiers and young professionals. They are living in urban neighborhoods which are characterized by a high proportion of rental housing; single-person and childless households (even though car-sharers may live with a partner or children themselves); pedestrian friendliness; and relatively high density. This suggests, then, that the most rewarding path for analysis is to focus on neighborhood and transportation characteristics that promote car-sharing, rather than on finding neighborhoods that match the individual demo- graphic characteristics of car-sharing members. For example, even though high education levels are one of the hallmarks of car-sharing members, the neighborhoods with the highest percentages of college graduates may not be the most fertile turf for car-sharing. Indeed, both Flexcar and City CarShare have been forced to close pods in Palo Alto, CA – home of Stanford University and one of the most highly educated communities in the United States. Instead, certain transportation characteristics may be the most important to identifying potential markets for car-sharing. Variables such as commute mode split, household composition and – in particular – vehicle ownership seem to be the best proxies for the types of neighborhoods where car-shar- ing succeeds. They indicate places where transit and walking are realistic alternatives, and where a car is not needed for everyday travel. They also indicate places that attract a high proportion of single, childless households. Specifically, average vehicles per household and number of people who walk to work within a half mile of a pod location appear to be the most important variables for predicting car-sharing success as determined in the multiple-regression analysis. The percentage of households with no or one . Aspen, Boston, Denver-Boulder and New York also have over 0% of households earning more than $00,000 per year.

Car-Sharing: Where and How It Succeeds Page 3-39 vehicle also appears to have a strong, non-linear relationship with car-shar- ing success (see Appendix B). Surprisingly, physical factors such as density, intersection density and age of housing do not stand out as primary indicators. The role of density is discussed in more detail in the next section. Role of Density The results provide some conflicting suggestions about the overall im- portance of residential density. This variable is clearly important in some manner for car-sharing. As noted above, it is an indication of the potential customer base for a pod – doubling the density will double the number of customers within walking distance. It also serves as a good proxy for the auto-orientation of a neighborhood. Holtzclaw et al. (2002), for example, found that residential density served as the best predictor of vehicle travel, explaining 63%-86% of the variation in vehicle miles traveled in San Fran- cisco, Los Angeles and Chicago. However, the density levels for pod neighborhoods are far below what might be expected from a review of other research. For example, 25% of pod neighborhoods have a density of 8.5 households/acre or less. For comparison, single-family “sprawl” often clocks in at around three units to the acre, while San Francisco Bay Area data suggest that transit ridership increases noticeably at 10 households per residential acre (Holtzclaw, 2002). A threshold of 15-25 units per acre is often cited as a desirable minimum for transit oriented development, while 4-6 units/acre appears to be the minimum for even basic hourly frequencies (for a broader discussion, see Kuzmyak et al., 2003; Dittmar & Poticha, 2004). One explanation may be that many pods are situated close to rail stations with large amounts of surface parking, which lowers gross densities, or are in mixed-use centers with lower residential densities but a large daytime population. Certainly, relatively high walking rates (22% on average for all pod neighborhoods) suggest a predominance of mixed-use development. However, it is also possible that density is not as dominant in explaining car-sharing market settings as it is, for example, in the case of transit. Car-Sharing Thresholds In summary, then, how can a current or would-be car-sharing operator, or a transit agency or other partner organization, assess the types of neigh-

Chapter 3 • Market analysis September 2005 Page 3-40 borhoods where car-sharing may be viable? Some guidelines, based on the analysis in preceding sections, are shown in Exhibit 3-15, which shows two sets of thresholds: low service, where car-sharing may be viable but where limited growth can be expected, and high service, where car-sharing is likely to flourish. These thresholds are not precise requirements. Rather, they are intended as guidelines to show the approximate neighborhood characteristics that help to sustain car-sharing.3 There are certainly examples of successful car- sharing operations that do not meet these thresholds, particularly in the special niches discussed earlier in this chapter. However, these guidelines can assess the extent to which neighborhoods do have supportive charac- teristics. Combined with the other considerations discussed in Chapter 8, such as support from partner organizations, they can help determine the likelihood of success. Exhibit 3-15 Guidelines for Where Car-Sharing Succeeds Variable Level of Service Low High* Demographics % 1-person households 30% 40%-50% Commute Mode Share % drive alone to work 55% 35%-40% % walk to work 5% 15%-20% Vehicle Ownership % households with no vehicle 10%-15% 35%-40% % households with 0 or 1 vehicle 60% 70-80% Neighborhood Characteristics Housing units per acre 5 5 * High service roughly equates to 10 or more car-sharing vehicles within a half-mile radius. Note: For most variables, the values are the suggested minimums that are needed to achieve a given level of car-sharing service. For the “% drive alone to work” variable, the values are the suggested maximums. . These values were approximated from analyzing percentiles and scatter plots for each variable.

Car-Sharing: Where and How It Succeeds Page 3-41 3.3 Growth potential While car-sharing is a niche product at present, the potential for growth has excited many researchers. A range of market demand studies, conducted principally in Europe, has estimated a market potential of anything from 3% to 25% of the population. Most of these studies have identified the segments of the population that would use car-sharing – often based on survey data – and then used this to estimate total market potential. For example: • United States. A 2004 study of the market potential in Baltimore, MD suggests that car-sharing could replace at least 4% of private vehicles. This simulation was based purely on cost savings; for more than 4% of vehicles, car-sharing would be cheaper than ve- hicle ownership (Schuster et al., 2005). • Austria. The minimum market potential for “pioneer house- holds” was estimated at 13.5% of households in two urban resi- dential neighborhoods in Graz, based on the following criteria (Steininger, Vogl & Zettl, 1996): o Age between 25 and 43 o University degree or equivalent o Own at least one car, but not in a high price bracket o Yearly car mileage of one car below 15,000 km o Share of trips by car less than 33% o Current participation in environmental activities • The same study estimated the maximum market potential in the same neighborhoods at a far higher level – 69%. This estimate was based on the assumption that the decision to join a car-sharing program would be made solely on rational economic grounds: 69% of households had at least one car driven less than 15,000 km per year and would thus probably realize cost savings from car- sharing. • Germany. The potential market demand was estimated at 3% of the population, or approximately 2.45 million people (Baum & Pesch, cited in Shaheen, Sperling & Wagner, 1998). • Sweden. The “theoretical potential” was estimated at 25% of households, based on those who could travel to work by non-auto modes, without prolonging their commute time by more than 30 minutes. The “practical potential” was estimated at 5.6%, based on market research surveys asking if a household would be prepared to join a car-sharing organization. Both the “theoretical” and “practical” potential were limited to households possessing the following characteristics: living in communities of at least 10,000 inhabitants; at least one household member between the ages of 18

Chapter 3 • Market analysis September 2005 Page 3-42 and 70; and at least one person in the household having a driver’s license (Vägverket, 2003). • Switzerland. The market potential was estimated at 1.7 mil- lion members, or 23% of the population, based on three criteria (Muheim & Partner, 1998): o Possession of a driver's license o A residence that is not too remote (living in the developed zones of municipalities with at least 2,000 inhabitants) o A journey to work that does not have to be made by car (jour- ney to work would not be lengthened by more than 30 min- utes) In reality, despite impressive growth rates, the actual take-up has fallen far short. Current membership rates are a factor of 12 to 30 times lower than those forecast about a decade ago (Harms, 1998). Mobility Switzerland, for example, had about 60,000 customers in November 2003 (Mobility Swit- zerland, personal communication) – 3.5% of the forecast potential. At least partly, this appears to be due to the “routine” nature of car use; as discussed earlier in this chapter, many members appear to join following a “trigger event” such as moving residence or changing jobs. Again, this evidence tends to give further support to the conclusion from the analysis of market typologies. Rather than solely being informed by the characteristics of potential members, market potential studies should focus more on whether neighborhood characteristics will allow car-sharing to be successful. They should also consider whether the institutional characteris- tics are in place, i.e. the depth of support from partner organizations. These issues are explored in the following chapters.

Car-Sharing: Where and How It Succeeds Page 3-43 references Baum, H. and Pesch, S. (1994). Untersuchung der Eignung von Carsharing im Hinblick auf die Reduzierung von Stadtverkehrsproblemen. Bonn: Bundesminis- terium für Verkehr. Cited in Shaheen, Sperling & Wagner (1998). Berge, Guro (1999), Bilkollektivet i Oslo. Oslo: Transportøkonomisk Insti- tutt. Bonsall, Peter (2002). Car Share and Car Clubs: Potential Impacts. Institute for Transport Studies, University of Leeds. Report prepared for DTLR and Motorists’ Forum. Brook, David (1999). “So You Want to Start a Car Sharing Service?” World Transport Policy & Practice, 5(4): 202-210. Brook, David (2004). Carsharing – Start Up Issues and New Operational Models. Paper presented at Transportation Research Board 83rd Annual Meeting, Washington, DC, January 11-15, 2004. Cairns, Sally; Sloman, Lynn; Newson, Carey; Anable, Jillian; Kirkbride, Alistair; and Goodwin, Phil (2004). "Chapter 8. Car Clubs," in Smarter Choices – Changing the Way We Travel. London: Department for Transport. Carplus (2004). Putting Cars in the Mix. Development and Impacts of Car Clubs in Rural Areas. Final Report of the Carplus National Rural Transport Partner- ship, 2001-2004. Leeds: Carplus. Accessed June 13, 2005 at www.carclubs. org.uk/carclubs/rural-clubs.htm The Countryside Agency (2004). Rural Car Clubs. Cheltenham: The Coun- tryside Agency. Accessed June 13, 2005 at www.countryside.gov.uk/Publica- tions/articles/Publication_tcm2-21421.asp Dittmar, Hank and Poticha, Shelley (2004). “Defining Transit-Oriented Development: The New Regional Building Block,” in Dittmar, Hank and Ohland, Gloria (eds), The New Transit Town: Best Practices in Transit-Oriented Development, pp 20-40. Washington, DC: Island Press. Elmore-Yalch, Rebecca (1998). TCRP Report 36: A Handbook: Using Market Segmentation to Increase Transit Ridership. Washington, DC: Transportation Research Board. Grossberg, Rebecca and Newenhouse, Sonya (2002). Community Car: A New Transportation Option for Madison, Wisconsin: Carsharing Feasibility Study. Madison Environmental Group, Inc., September 2002.

Chapter 3 • Market analysis September 2005 Page 3-44 Harms, Sylvia (2003). From Routine Choice to Rational Decision Making Between Mobility Alternatives. Paper presented at the 3rd Swiss Transport Research Conference. Monte Verità / Ascona, March 19-21, 2003. Harms, Sylvia and Truffer, Bernard (1998). The Emergence of a Nationwide Carsharing Co-operative in Switzerland. Prepared for EAWAG – Eidg. Anstalt für Wasserversorgung. Abwasserreinigung und Gewasserschutz. Switzer- land. Holtzclaw, John (2002), How Compact Neighborhoods Affect Modal Choice – Two Examples. Available at: www.sierraclub.org/sprawl/articles/modal.asp. Holtzclaw, John; Clear, Robert; Dittmar, Hank; Goldstein, David; and Haas, Peter (2002). “Location Efficiency: Neighborhood and Socio-Economic Characteristics Determine Auto Ownership and Use – Studies in Chicago, Los Angeles and San Francisco,” Transportation Planning and Technology, 25 (1): 1-27. Hope, Steven (2001). Monitoring and Evaluation of the Edinburgh City Car Club. Edinburgh: Scottish Executive Central Research Unit. Jensen, Nicole (2001), The Co-operative Auto Network Social and Environmental Report 2000-01. Vancouver: Co-operative Auto Network. Katzev, Richard, Brook, David and Nice, Matthew (2000), “The Effects of Car Sharing on Travel Behaviour: Analysis of CarSharing Portland’s First Year,” World Transport Policy & Practice, 7(1): 22-26. Klintman, Mikael (1998). Between the Private and the Public. Formal Car Sharing as part of a Sustainable Traffic System. An Exploratory Study. KFB Meddelande 1998:2. Stockholm: Kommunikationsforskningsberedning. Koch, Henning (2002). MOSES User Needs Report. Accessed March 29, 2004 at http://213.170.188.3/moses/m_papers/USER_NEEDS_REPORT_new.pdf Kuzmyak, J Richard; Pratt, Richard H; Douglas, G Bruce; and Spielberg, Fran K. (2003). TCRP Report 95: Traveler Response to Transportation System Changes. Chapter 15 – Land Use and Site Design. Washington, DC: Transpor- tation Research Board. Lane, Clayton (2004). PhillyCarShare: First-Year Social and Mobility Impacts of Car Sharing in Philadelphia. Paper presented at Transportation Research Board 84th Annual Meeting, Washington, DC, January 9-13, 2005.

Car-Sharing: Where and How It Succeeds Page 3-45 Meaton, Julia and Low, Christopher (2003). “Car Club Development: The Role of Local Champions,” World Transport Policy & Practice, 9(3): 32-40. Mobility Switzerland (2004). ”Kriterien für die Standorteröffnung,” Mobility Journal, April 2004. Muheim, Peter & Partner (1998). CarSharing – the Key to Combined Mobility. Swiss Federal Office of Energy, Energie 2000. Accessed March 29, 2004 at reservation.mobility.ch/mobilmanager/IntSummeryE.html Polk, Merritt (2000), Carsharing in Sweden: A Case Study of the Implementation of an Internet Booking System in Majornas Car Cooperative in Göteborg. Stock- holm: Vägverket. Reutter, Oscar and Böhler, Susanne (2000). “Car Sharing for Business: The Aachen Region Pilot Project.” World Transport Policy & Practice, 6(3): 11-17. Robert, Benoît (1999). “Developing Carsharing in a Hostile Environment. The Virtues of Pragmatism,” World Transport Policy & Practice, 5(4): 223-237. Robert, Benoît (2000). Potentiel de l’auto-partage dans le cadre d’une politique de gestion de la demande en transport. Paper presented at Forum de l’AQTR, gaz à effet de serre: transport et développement, Kyoto: une opportunité d’affaires?, Montréal, February 7 2000. Schuster, Thomas; Byrne, John; Corbett, James; and Schreuder, Yda (2005). Assessing the Potential Extent of CarSharing in the United States: A New Method and Its Implications. Paper presented at Transportation Research Board 84th Annual Meeting, Washington, DC: January 9-13, 2005. Schwieger, Bodo (2004). International Developments towards Improved Car- Sharing Services. Oxford: Writersworld. Shaheen, Susan; Schwartz, Andrew; and Wipyewski, Kamill (2004). “Policy Considerations for Carsharing and Station Cars: Monitoring Growth, Trends, and Overall Impacts,” Transportation Research Record 1887, pp 128-136. Wash- ington, DC: Transportation Research Board. Shaheen, Susan, Sperling, D. and Wagner, Conrad (1998), “Carsharing in Europe and North America: Past, Present and Future,” Transportation Quar- terly, 52(3):35-52. Steininger, Karl; Vogl, Caroline; and Zettl, Ralph (1996). “Car-Sharing Orga- nizations: The Size of the Market Segment and Revealed Change in Mobility Behavior.” Transport Policy 3(4): 177-185.

Chapter 3 • Market analysis September 2005 Page 3-46 Toor, Will and Havlick, Spenser W. (2004). Transportation and Sustainable Campus Communities. Washington, DC: Island Press. Vägverket (2003). Make Space for Car-Sharing! Publ. No. 2003: 88E. July 2003. Stockholm: Vägverket.

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TRB’s Transit Cooperative Research Program (TCRP) Report 108: Car-Sharing--Where and How It Succeeds examines development and implementation of car-sharing services. Issues addressed in the report include the roles of car-sharing in enhancing mobility as part of the transportation system; the characteristics of car-sharing members and neighborhoods where car-sharing has been established; and the environmental, economic, and social impacts of car-sharing. The report also focuses on car-sharing promotional efforts, barriers to car-sharing and ways to mitigate these barriers, and procurement methods and evaluation techniques for achieving car-sharing goals.

Appendices A through E of TCRP Report 108 are included with the report on CRP-CD-60 that is packaged with the report. The appendices include an annotated bibliography; a list of partner organizations surveyed and interviewed; survey instruments; and sample documents such as Requests for Proposals (RFPs) and zoning ordinances related to car-sharing. Appendix E was designed as a resource for introducing organizations to car-sharing and encouraging partnerships to initiate car-sharing programs.

Links to the download site for the CRP-CD-60 and to instructions on burning an .ISO CD-ROM are below.

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(Warning: This file is large--23.9 MB--and will take approximately 15 minutes to download using a high-speed connection.)

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