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

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About: Free-floating carsharing users’ willingness-to-pay/accept for logistics management mechanisms Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Free-floating carsharing users’ willingness-to-pay/accept for logistics management mechanisms
Creator	Tang, William Le Vine, Scott Philips, Sandra Polak, John Wu, Chenyang
Source	Elsevier; Medline; PMC
abstract	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.
has issue date	2020-07-08(xsd:dateTime)
bibo:doi	10.1016/j.tbs.2020.06.008
bibo:pmid	32835002
has license	no-cc
sha1sum (hex)	a27d98a48d3c004567ba512d208577072bdd7c97
schema:url	https://doi.org/10.1016/j.tbs.2020.06.008
resource representing a document's title	Free-floating carsharing users’ willingness-to-pay/accept for logistics management mechanisms
has PubMed Central identifier	PMC7345391
has PubMed identifier	32835002
schema:publication	Travel Behav Soc
resource representing a document's body	covid:a27d98a48d3c004567ba512d208577072bdd7c97#body_text
is schema:about of	named entity 'Regression analysis' named entity 'Survey' named entity 'specific' named entity 'Washington D.C.' named entity 'generally' named entity '2017' named entity 'Vancouver' named entity 'accept' named entity 'FLEETS' named entity '311' named entity 'GENERALLY' named entity 'INCENTIVES' named entity 'TIMES' named entity 'periods' named entity 'incentives' named entity 'stock' named entity 'features' named entity 'user' named entity 'flexibility' named entity 'users' named entity 'logistics management' named entity 'user experiences' named entity 'incentivisation' named entity 'socio-demographic' named entity 'incentivisation' named entity 'carsharing' named entity 'locations' named entity 'Namazu' named entity 'carsharing' named entity 'incentive program' named entity 'OLS' named entity 'variance inflation factor' named entity 'user experience' named entity '2.0' named entity 'parameter estimates' named entity 'travel behaviour' named entity 'dependent variables' named entity 'modes of transport' named entity 'Travel Behaviour' named entity 'independent variables' named entity 'Travel Behaviour' named entity 'vehicle pick-up' named entity 'statistically significantly' named entity 'policy-makers' named entity 'statistically significant' named entity 'correlation' named entity 'logistics management' named entity 'incentivisation' named entity 'non-normality' named entity 'WTA' named entity 'price level' named entity 'Likert scale' named entity 'ordinary least squares' named entity 'WTA' named entity 'Makwana' named entity 'correlation' named entity 'Contingent valuation methods' named entity 'staff member' named entity 'incentivisation' named entity 'independent variables' named entity 'logistics' named entity 'significance level' named entity 'WTA' named entity 'WTA' named entity 'Carsharing' named entity 'effective sample size' named entity '4.3' named entity 'Vancouver' named entity 'incentivisation' named entity 'Shapiro-Wilk test' named entity 'WTA' named entity 'carsharing' named entity 'carsharing' named entity 'parameter estimates' named entity 'socio-demographic' named entity 'linear regression' named entity 'user experience'

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