[Paper Review] Potential of on-demand services for urban travel

Nejc Geržinič, Niels van Oort+3 more|arXiv (Cornell University)|Jul 2, 2021

Transportation and Mobility Innovations44 references9 citations

TL;DR

This study assesses the potential of on-demand mobility services in urban areas using a stated preference survey with 1,063 respondents in the Netherlands. It identifies four traveler segments—Sharing-ready cyclists (55%), Tech-ready (27%), Flex-ready (9%), and Flex-sceptic (9%)—revealing that only a minority would adopt on-demand services, with adoption driven by speed or cost sensitivity, suggesting limited overall modal shift and potential for increased vehicle miles traveled if not carefully managed.

ABSTRACT

On-demand mobility services are promising to revolutionise urban travel, but preliminary studies are showing they may actually increase total vehicle miles travelled, worsening road congestion in cities. In this study, we assess the demand for on-demand mobility services in urban areas, using a stated preference survey, to understand the potential impact of introducing on-demand services on the current modal split. The survey was carried out in the Netherlands and offered respondents a choice between bike, car, public transport and ondemand services. 1,063 valid responses are analysed with a multinomial logit and a latent class choice model. By means of the latter, we uncover four distinctive groups of travellers based on the observed choice behaviour. The majority of the sample, the Sharing-ready cyclists (55%), are avid cyclists and do not see on-demand mobility as an alternative for making urban trips. Two classes, Tech-ready individuals (27%) and Flex-ready individuals (9%) would potentially use on-demand services: the former is fairly time-sensitive and would thus use on-demand service if they were sufficiently fast. The latter is highly costsensitive, and would therefore use the service primarily if it is cheap. The fourth class, Flex-sceptic individuals (9%) shows very limited potential for using on-demand services.

Motivation & Objective

• To understand the demand for on-demand mobility services in urban settings.
• To assess the potential impact of on-demand services on current modal choice patterns in cities.
• To identify distinct traveler segments based on preferences for on-demand mobility.
• To evaluate whether on-demand services could increase vehicle miles travelled and worsen congestion.
• To inform urban mobility planning by identifying adoption drivers and barriers.

Proposed method

• A stated preference survey was administered to 1,063 respondents in the Netherlands, presenting choices among bike, car, public transport, and on-demand services.
• Multinomial logit and latent class choice models were applied to analyze the survey data and uncover unobserved heterogeneity in travel behavior.
• The latent class model identified four distinct traveler segments based on their response patterns to service attributes such as speed and cost.
• Model parameters were estimated to quantify the influence of time and cost on the probability of choosing on-demand services.
• The analysis compared the predicted modal shares under current conditions and with on-demand service availability.
• The study used a discrete choice modeling framework to assess the potential for modal shift and service adoption.

Experimental results

Research questions

• RQ1 What proportion of urban travelers would adopt on-demand mobility services under different service attributes?
• RQ2 How do traveler preferences for on-demand services vary across distinct behavioral segments?
• RQ3 What are the key determinants—speed, cost, or convenience—that influence on-demand service adoption?
• RQ4 To what extent might on-demand services displace public transport or cycling, potentially increasing vehicle miles travelled?
• RQ5 How can urban planners design on-demand services to minimize congestion and maximize sustainable mobility?

Key findings

• The majority of respondents (55%) are Sharing-ready cyclists who are unlikely to switch from cycling to on-demand services, regardless of service quality.
• 27% of respondents are Tech-ready individuals who would adopt on-demand services primarily if they are fast enough to save time.
• 9% of respondents are Flex-ready individuals who would use on-demand services only if they are sufficiently low-cost.
• Another 9% are Flex-sceptic individuals who show minimal interest in on-demand services, regardless of price or speed.
• The study suggests that on-demand services may not significantly reduce car use or vehicle miles travelled, especially if they replace cycling or public transport.
• The results indicate that on-demand services are unlikely to achieve high modal share without strong incentives tied to speed or cost.