Free-floating carsharing users’ willingness-to-pay/accept for logistics management mechanisms

• Published in: Travel, behaviour & society behaviour & society, 2020-10, Vol.21, p.154-166
• Main Authors: Wu, Chenyang, Vine, Scott Le, Philips, Sandra, Tang, William, Polak, John
• Format: Article
• Language: English
• Subjects: Free-floating carsharing; User-based relocation; Willingness-to-pay/accept
• ISSN: 2214-367X; 2214-3688
• DOI: 10.1016/j.tbs.2020.06.008

•We study four user-based relocation mechanisms for free-floating carsharing.•We document FFCS users’ willingness-to-pay/accept (WTP/WTA) for the four mechanisms.•We demonstrate that user experience variables significantly correlate with WTP/WTA. The spatio-temporal flexibility of free-floating carsharing (FFCS) fleets leads to vehicle stock imbalances across the network. One set of strategies for managing fleet distribution involves incentivising users to participate in relocating the vehicles. The objective of this study is to establish FFCS customers’ preferences for each of four incentivisation mechanisms: 1) vehicle delivery, 2) paid relocation, and 3–4) incentivisation for alternate vehicle pick-up and drop-off locations. Survey data (n = 311; collected Sept. 2017) from FFCS users in Vancouver and Washington D.C. are employed to quantify willingness-to-pay/accept (WTP/WTA) for these mechanisms. We find that a majority of respondents report positive attitudes (“definitely” or “possibly” willing to use) toward each of the four incentivisation mechanisms, with alternate drop-off the highest (57%) and paid relocation the lowest (40%). Regression analysis finds that user experiences using FFCS are generally stronger predictors of WTP/WTA than socio-demographic features, with (intuitively) the frequency of FFCS unavailability the strongest predictor. Age is the strongest socio-demographic predictor, with the WTP for vehicle delivery increasing and the size of required incentives for alternate pick-up/drop-off locations decreasing with age. Finally, we performed k-means cluster analysis of respondents based on the times-of-week that they report experiencing difficulty finding an available FFCS vehicle, and identified four distinct segments of users. However, we found generally weak relationships between WTP/WTA and the specific time-of-week periods that unavailability is experienced.