Is ride-hailing competing or complementing public transport? A perspective from affordability
Introduction
Urban passenger transportation contributes a significant source of fossil energy consumption and greenhouse gas (GHG) emissions. Across different passenger transport modes, vehicle occupancy rate is recognised to largely explain the environmental impact and itself elaborates approximately 70 %–90 % of the variation around average energy and GHG intensity between transport modes (Schäfer and Yeh, 2020). Owing to the potential benefits from using public transit, densely populated areas in large cities are typically designed as public transport-oriented development to increase the public transit ridership so as to reduce energy consumption and carbon emissions substantially. Especially under the strategic goal of achieving peak carbon dioxide emissions and thereafter carbon neutrality in 2030 and 2060, respectively, as proposed by China at the U.N. General Assembly (Commission, 2021), how to achieve low-carbon development in the transport industry is particularly important.
However, since the last decade, the emergence of ride-hailing service may frustrate this goal. If ride-hailing mode attracts a large number of passengers from public transit, the occupancy rate of public transit will decrease and thereafter lead to an increase in energy consumption and GHG emission intensity per passenger per kilometre. Pertinent literature raised the concern that whilst competing with automobile-dependent transport (including private car travel and traditional taxi services), the ride-hailing service also substitutes a considerable part of public transit (mainly including metro and buses) (Gehrke et al., 2019, Kong et al., 2020, Liao, 2021, Qiao and Yeh, 2021, Rayle et al., 2016, Welch et al., 2020, Young and Farber, 2019).
This intensifying debate on the modal shifts between ride-hailing and public transit, raised concerns about the negative environmental effects of the potential decline in public transit ridership (Jin et al., 2018). It opens an important question that, how many trips have shifted from public transport to ride-hailing? The number alarms to what extent public transport policies need to be transitioned to attract passengers, from a simple way of subsidies to a hard way like transit innovation.
To answer this question, the study touches on an important determinant, that is, the differences in expenses between public transit and ride-hailing is so significant, why do transit-dependent people turn to use ride-hailing? It is by occasional or a steady routine?
One travel survey in California provides the clue from the affordability perspective (Brown, 2019). The research divided zero-car households into car-less and car-free families. The former one, car-less families typically are unable to afford automobiles and use ride-hailing as an alternative for their automobile travel occasionally. While the latter one, car-free families abandon the purchase of vehicles due to the embrace of car-free lifestyle. Car-free families liberate from owning cars, but they can still freedom travel in the cities by affording other transport means like ride-hailing and taxi. Overall, economic restrictions remain the biggest influences on travel choices.
Therefore, the economic status reflects the ability to afford travel cost (e.g., owing private car) and plays a key role in choosing ride-hailing and its alternatives. In this research, we utilized affordability to refer to individual economic status. However, the inherent flaw of big data, i.e. the lack of personal information, makes the economic status less investigated in big data-driven research. Thus, this study introduces the affordability as a supplementary influencing factor beyond the physical conditions of public transit availability by following previous big data research on the modal shifts of ride-hailing (Kong et al., 2020, Liao, 2021).
To compensate for the missing personal information in big data research, we propose an integration of both small and big data to estimate substitution preferences for different income groups. The core is to differentiate the residents have the similar affordability by their living residences. Then the similar affordability represents a particular collective mobility constrain.
A questionnaire survey consisting of 706 valid respondents derives the travel preferences of ride-hailing and substitute willingness between ride-hailing and other transports (private car, traditional taxi, metro, bus). We also consider the impact of travel purposes (working and leisure) on the willingness of using ride-hailing as it is one of the determinants of choosing ride-hailing (Brown, 2019). In a wide sense, this study utilizes working and leisure travel to represent the regular and irregular travel behaviours that affected by different expectations of travel time, traveling expense, comfort, and convenience (Manley et al, 2018). Three specific research questions have been answered respectively:
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How does affordability affect ride-hailing usage? Would the effects change with travel purposes? (From questionnaire)
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How does affordability affect alternative travel choices for ride-hailing? (From questionnaire)
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How many trips have shifted from public transport (metro and bus) to ride-hailing? (Linking questionnaire to big data)
To this end, this study utilized a big data resource of ride-hailing travel trips in Chengdu, combined with travel questionnaires, to evaluate the modal shifts between ride-hailing, private and public transport at the trip-based level. In particular, the concept of affordability is introduced to obtain the weighted measure of the travel attitudes and alternative preferences for residents living in different income-level neighbourhoods. It emphasises that the heterogeneity for different income groups is a basic consideration for assessing the travel preferences. Then, we calculated the housing price as the indicator of affordability to represent economic status to differentiate the substitution willingness of ride-hailing on private and public transport for different income groups. Finally, this study tells how many ride-haling trips are shifted from public transport. For policy makers whose mission is to promote low-carbon transport systems vigorously, the answer would help lead the cities to a sustainable future.
Section snippets
Background
The rise of ubiquitously available ride-hailing reshaped the urban landscape into a new era of travel that travellers can have an alternative option for a flexible taxi-like intra-city trip even without the private car. However, the consequences brought by the new ride-hailing mobility are not only a substitute for personalised automobile travel but also a competition for public transit.
The literature on the relationship between ride-hailing and other travel means indicates that the former
Study area and data
Chengdu, the capital city of Sichuan Province in Southwest China, is used as the case study. We conducted the questionnaire survey with street interviews in Chengdu in November 2021. The locations of the street interviews are selected by two criteria. Firstly, the distribution of neighbourhood samples must be dispersed in the study area to ensure our samples’ representativeness. Secondly, the sampled neighbourhoods should be able to represent different income groups. We identified 63 locations
Housing price and affordability
First, we verified whether residential housing price represents differentiated affordability through questionnaires. In Table 2, the preliminary observation from the questionnaires is that neighbourhoods with higher housing price inhabited higher income populations who spend more monthly travel cost, and this relationship significantly differs across neighbourhoods through F-test. It verifies that housing price is an efficient and appropriate proxy of representing affordability in our study. In
Conclusions
The objective of a green and low-carbon transport system is essential in developing sustainable cities and achieving the 11th goal of SDGs in the future (Assembly, 2015, Commission, 2021). To alleviate the air pollution and energy consumption induced by increasing burden of urban transport systems, the transit-oriented development in urban planning becomes the most welcomed strategy. However, the emergence of ride-hailing may frustrate this goal as the evidence shows it is attracting people to
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgment
We would like to thank the financial support from the Dissertation Fellowship of Peking University-Lincoln Institute Center for Urban Development and Land Policy (Grant Number DS04-20211001-QS); Chan To-Haan Endowed Professorship Fund of the University of Hong Kong; "Sustainability, Inequality, Mobility and Accessibility in Mega-City Regions", Joint Programming Initiative (JPI) Urban Europe and National Natural Foundation of China (NSFC), Grant Number: 71961137003; and Guangdong–Hong Kong-Macau
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