Title: Welfare in Ride-hailing and Decision on Private Transport Mode

Introduction

Singapore’s car prices are the highest in the world with it being around 4-5x costlier than in US or Korea. The rise of ride-hailing platforms such as Uber and Grab since 2013 has caused a shift from the usual private transport modes of cars and traditional taxis to ride-hailing.

In 2019, Singapore had about 77 thousand private hire automobiles, both self-drive and chauffeured (Müller, 2021). The increased number of private-hire cars is tied to Singapore’s booming ridehailing industry. Despite that, Singapore has seen a decrease albeit not significant in private car ownership from over 607,292 in 2013 to 556,155 in 2019 (Müller, 2021).

It is undeniable that public transport would be the cheapest alternative for consumers in Singapore as compared to other countries. However, it seems that despite the government’s push for Singaporeans to switch over to mass transit, there is still a considerable number of vehicles on the road. As such we can see that there is still a high value placed on private transport in Singapore.

Ride-hailing is essentially commuters paying to ride in the personal vehicles of other drivers to reach their destinations. As compared to regular taxis, ride-hailing platforms offer lower fares. These platforms promote efficient matching of passenger to driver through mobile application which reduces the search cost of street hailing.

Drivers save on cost of searching of passengers and passengers save time on searching for driver. Ride-hailing platforms include ride-sharing services where the driver can pick up more passengers who are on the same route, therefore maximizing vehicle capacity. It also conserves fuel and cuts the quantity of carbon emissions created by single-occupancy vehicles. Ridesharing helps to further alleviate traffic congestion on the roads.

This paper is interested in examining the welfare implication of dynamic pricing, a key element in ride-hailing. Next, ride-hailing being a closer and better alternative as compared to traditional taxi’s, I aim to examine an individual’s decision between car ownership and ride-hailing.

Importance of ride-hailing

Moral hazard is the tendency of a better-informed party to exploit its information advantage in an undesirable or dishonest way. Before the entry of ride-hailing platforms, it was difficult to monitor taxi drivers. In the taxi industry, taxi drivers are more familiar with the routes to the destination of his passenger.

As such, the taxi driver tends to detour on a longer route to increase the distance-based fare and adjust to slower speeds to increase the time-based fare. Introduction of ride-hailing services served to alleviate the information costs in the taxi industry. Through the ride-hailing app, passengers can monitor the route taken by the driver and easily file a complaint.

When an individual requests for a ride, the app is able to automatically calculate the price of the trip which riders can immediately see and decide on whether to accept the price. This prevents drivers from adjusting to slower speeds to increase the time-based fare since it will not affect the price of the trip. As such, ride-hailing platforms help to reduce moral hazard in taxi drivers.

Besides that, the driver rating mechanism in the platform serves as a deterrent for drivers to provide low quality service. Because of the advent of ride sourcing systems, a previously unrated transportation service can now be rated, offering a measure of service quality.

The ratings have an impact on both passengers and drivers’ conduct, playing a key role in the dispatching priority and whether or not drivers are allowed to work on the platform (Wang & Yang, 2019). Grab for example, requires drivers to maintain a star rating of 4.5/5 to continue working on the platform.

Key feature of ride-hailing platform: Dynamic pricing

Rider waiting time and capacity utilization rate are linked to the concept of service reliability whereby sudden spikes in demand, such as a train disruption, can result in a dramatic increase in rider waiting time and a fall in capacity utilization rate, resulting in a negative experience on both rider and driver (Yan et al., 2019).

Ride-hailing platforms utilize dynamic pricing which is the dynamic adjustment of prices for rides based on real-time demand and supply conditions to increase market efficiency and reliability. The platforms commonly refer to this as “surge pricing”. When the demand exceeds supply,

those who need a ride urgently and are willing to pay the premium can be matched to a driver. This dynamic pricing is utilized mainly to prevent the phenomena known as the “Wild Goose Chase” (WGC). When there are not enough drivers to meet demand, available drivers are activated as soon as possible. In a supply-constrained circumstance, drivers may be dispatched to much further pickup sites under the first-dispatch protocol (Yan et al., 2019).

This leads to longer pickup time, resulting in additional fuel usage and lower passenger capacity utilization which reduces driver’s earnings. Drivers then exit the platform in response to reduced earnings which starts a feedback cycle. Figure 1 illustrates the WGC phenomenon.

Welfare

This section will examine welfare effects of dynamic pricing. Firstly, the platform’s revenue is the fraction it takes from price of the trip multiplied by the total number of trips. That is, at equilibrium price p and Q trips, 𝜃𝑝𝑄. Note that 𝜃 is fixed.

To define driver and rider surplus, I am concerned with number of trips and pickup time hence let U(Q, L, T) be the aggregate utility whereby T is the average pickup time, Q is the number of trips and L is the labor supply.

Assumption: Utility is decreasing in T as utility is greater when people are served with lower pickup times. Utility is increasing in Q as utility is greater when people are served with more trips. Furthermore, an equilibrium with lower pickup times requires higher prices such that customers with higher willingness to pay would be served.

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