Abstract
With the development of Internet technology, online car-hailing is booming in China, which has profoundly affected people’s travel structures. In order to seek the sustainable development of taxi and online car-hailing services from the perspective of passenger mode choice behavior, the mechanism of passengers’ decision-making procedures and their travel mode choice behaviors were analyzed. To study the influence of latent variable factors on passenger choice behavior, this paper firstly designed a questionnaire, and a structural equation model (SEM) was established for the preliminary study of the relationship between the latent variables and the behavioral intentions using the online survey data. Then, the latent variables were introduced into the Logit model, setting up the SEM-Logit model to explore the mode choice patterns between taxis and online car services. The results showed that the SEM-Logit model with the latent variables is better than a general Logit model in terms of the model precision and hit ratio. Meanwhile, after introducing the latent variables, it was found that convenience, comfort, and economy factors have a significant influence on the model, and the explanatory power of the model increases accordingly.
Highlights
The trip mode choice is important in traffic demand analysis
Cui et al [2] analyzed the online order data of taxis and express services and found that, in terms of the travel time of taxi online orders, trips of less than 20 minutes account for 22.8% of all rides, trips of 20–30 minutes account for 24.5%, and trips of 30–40 minutes account for 21.2%
The model consisted of two parts—the first part was the structural equation model (SEM) model, which was mainly used to describe the causal relationship between the latent variables of travel mode selection and the corresponding observation variables
Summary
The trip mode choice is important in traffic demand analysis. Most factors that affect the trip mode choice can be directly observed, such as required cost, time, and other economic indicators, and have been widely applied in various research papers. Online car-hailing services realize the information required for matching of the driver and the passenger and reduce the proportion of customers searching. It can replace the private car travel needs of some high time value groups. Both online car-hailing services and taxis can provide personalized and door-to-door services (both of them are on-demand mobility services, and taxis can be used for street hailing [1]), some researchers have shown that there are certain differences in the travel characteristics between them. The hmoitnsuptoetsa. rFeuasrtfhoerrtmakoirneg, tohneahnodtsopffoat raerbeaassicfoalrlytackoinnsgisotennta.nFdroomff tahreesebravsiiccea-lilnydciocantsoisrtcehnat.raFcrtoemristtihcse osefrovniclien-eincdairc-ahtaoirlinchgasrearcvteicreisstiacnsdotfaxoins,litnhee cdaiffr-ehraeinlicnegs bseetrwvieceens tahnedmtaarxeisn, otthaesdoibffveiroeunsceass bbeettwweeeenn ttahxeims aanrde nsuobt wasaoybsvoiroutasxaiss abnedtwbeuesnest.axInistahnedsescuabswesa,ypsaossretnaxgiesrsanadrebaubsleest.oInditshteinsegucaisshest,hpeamsscelnegarelrys, ianrdeicaabtliengtothdatistthinergeuaisrhe stohmeme pcelresaornlya,l cinhdoiiccaetpinrgefetrheantcethsebreetwareeensothmeetwpoermsoondaels cthhoaticaerepdreiffifecreunltcteos dbeestwcreibeenwthitehtwobosemrvoadbelse tihnadticaarteodrsi.ffTichuelstetofadcteosrcsriabffeewctitthheopbassesrevnagbelersi’nmdiocdaetocrhso. iTcheeastetitfuacdteosr,swahffieccht itnhetupranssinenflgueernsc’ emtohdeerecshuolitcse. aTthtietupduersp, owsheiochf tihnistupranpienrflwueanscteo tehxeprleosruelhtso.wThpeopteunrtpiaolsefaocftothrsis(lpaatepnert vwaarsiabtolese,xspulcohreashtohwe apttoittuendteisalorfatchteorfese(lilnatgesnot fvpaarsisaebnlegse,rss)uacffhecatsththeechaottiicteubdeehsaovriotrhsefofretealxinisgsanodf opnalsisneencgaerr-sh)aaiflifnecgt. the choice behaviors for taxis and online car-hailing
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