Ridehailing’s role on transportation modes’ integration: the analysis of two Latin American cases
Since ride-hailing applications have emerged, already embedded in complex transportation systems, the vocation of the service has been discussed. Such apps, like DiDi, for instance (which operates under its own brand in Chile, Colombia, Peru, and Mexico, and under the name 99 in Brazil), mediate the interaction between drivers and passengers, providers, and users of private urban trips.
Once the trip starts and ends freely in space and time, there is a great diversity in the ways in which it can be done, as well as freedom of combination between different modes of transportation. Especially, a major pattern is noticed: the use of trips to access public transportation.
This article presents cases and data related to one of ride-hailing already consolidated uses: use to access traditional public transport, especially structural — consisting of BRT lines or rails.
Positive impacts
Such multimodal trips, known as first- or last-mile, are desirable not only to fuel public transportation but also to be more efficient for their users and society.
From an individual point of view, a person, when deciding which mode of transportation to use, probably chooses the mode that has the best combination among duration (speed), cost, versatility, and comfort (1). If this person can combine different means, the possibility of maximizing their welfare is increased. Such a person can save time, money, have more comfort, or a combination of factors.
From a social point of view, trips made solely by car or motorcycle are replaced, and a gain in urban accessibility is achieved. In Latin America, most medium-sized cities have insufficient public transport, given the logistical and financial challenges of operating in low-density locations. Buses, in particular, have low reliability and frequency. In those cities, where there are good rail infrastructure and bus capillarity, there is a struggle with problems resulting from growing demand, combined with low investment in infrastructure. Even worse is the situation of those whose distance between residence and employment is high, usually poorer people living on the outskirts of cities. In those places, the first and last miles with ride-hailing become interesting as car and motorcycle trips can be replaced with car and public transport, and increase the accessibility of those residing far from the subway (2).
São Paulo and Rio de Janeiro (Brazil): strong patterns
In São Paulo, for instance, approximately 10% of DiDi/99 trips start or end at subway or train stations or bus terminals.
It is evident that these are first/last mile trips when we look at their time pattern and geographical distribution.
In Image 1 below, the blue lines are trips that start anywhere and are destined for Tucuruvi Station, one of the final stations of the São Paulo Metro Blue Line, which connects the North Zone (residential) to the South Zone (residential), passing through downtown. It is possible to notice that the trips are destined for Northeast of the city, which is not served by the subway.
While station trips peak in the morning, those departing from stations peak in the late afternoon. This is another indication that these are first and last-mile trips, as they deviate from the three-peak distribution pattern (morning, lunch, and afternoon) of demand during a typical day. These curves can be seen in images 2 and 3 below.
Santiago (Chile): the same pattern emerges
After acquiring 99 in 2018, DiDi started its activities in other Latin American countries besides Brazil. In such countries, we have already perceived the same pattern of supplementarity with public transport described above.
In Santiago, where DiDi activities started in 2019, one can notice the same pattern. Today, approximately 7.5% of DiDi trips in the city start or end at Santiago Metro stations. Image 4 below shows where trips to Pudahuel station begin. Note that they start north and east of the station; to the west, there are other stations that should attract trips closer to them, and to the south the line continues, and there are stations closer to those who live in that region.
What next?
It is worth mentioning that first- and last-mile ride-hailing has enhanced its positive effects, such as increased accessibility, decreased demand for parking spaces, and even GDP, through increased accessibility (3).
Ride-hailing today opens the door to a future in which urban transport will be consumed as a service (Mobility as a Service, or MaaS). The existence of MaaS opens a window of change in the medium-term individual choice: People no longer have to worry about buying a car, a motorcycle, or a bicycle. This change in medium-term choice unfolds into short-term modal choices; that is to say, made at the precise time when someone decides which mode to use for a trip (4). Once you no longer own a car, you do not have the option of choosing to drive your own vehicle at the time of displacement and will compare the price, duration, and comfort of the modes at your disposal. For example: If a person decides to go to the market 500m from their house, they will not choose to go by car. Then, the chance that they will choose an active, collective mode, or use more than one mode on the same trip increases.
This is already seen in São Paulo, where ride-hailing users use 7.5 times more collective modes and 2 times more active modes than car and motorcycle drivers (5). In addition, people who do not own motor vehicles tend to drive less, even lowering their carbon footprint (6).
To move in this direction, we need to work today to create solutions that facilitate modal integration. For example, designated pick-up and drop-off points at stations do not only help to organize surrounding traffic, but also create ease of circulation and encourage users to adopt this behavior. Another way to reduce friction in modal shift is to have integrated modes of payment, allowing the passenger to use the same means of payment to pay for both trips, or to pay only once for both modes, or to gain discounts on one mode after using the other.
First- and last-mile ride-hailing has enhanced its positive effects, such as increased accessibility, decreased demand for parking spaces, and even GDP, through increased accessibility.
In order to go even further, we should work today to create mode integration solutions, such as designated pickup and dropoff points and integrated payment methods, besides regulation that is not restrictive.
References:
1Domencich, T. A., & McFadden, D. (1975). Urban travel demand: a behavioral analysis. (D. W. Jorgenson & J. Waelbroeck, Eds.) (1st ed.). Amsterdam; Oxford: North-Holland Publishing Company.
2https://blogs.worldbank.org/transport/how-can-shared-and-demand-mobility-complement-public-transit
3Haddad, E. A., Vieira, R. S., Jacob, M. S., Guerrini, A. W., Germani, E., Barreto, F., … & Sayon, P. L. (2019). A socioeconomic analysis of ride-hailing emergence and expansion in São Paulo, Brazil. Transportation Research Interdisciplinary Perspectives, 100016.
4McFadden, D. (1999). Rationality for Economists? Journal of Risk and Uncertainty, 19(1–3), 73–105.
5https://medium.com/para-onde-vamos/analisando-dados-da-od-2017-i-usu%C3%A1rios-de-aplicativo-s%C3%A3o-multimodais-f5bdbf509e4e
6Martin, E. W., & Shaheen, S. A. (2011). Greenhouse gas emission impacts of carsharing in North America. IEEE transactions on intelligent transportation systems, 12(4), 1074–1086.
