Mobility as a Service (MaaS) should replace private car ownership with mobility services such as shared cars or bikes. But what shared vehicle options do we have for the first mile outside of the city center? Almost none.

We’ll have a look at the costs or revenues structure of car, bike or scooter sharing and options we have to make these services profitable and therefore available in a wider area.

The desert begins right behind the city center: no shared cars, biked or scooters available
(c) Allan Swart

Like any company also shared fleet providers need to work profitably: revenues must be higher than the associated costs per vehicle rented out.

Revenues dependent on the frequency the vehicles get rented out and their rental price. The usage frequency is usually highest where the density of people is highest, i.e. in the city centers. It drops towards the outskirts. Another factor influencing the frequency is also how familiar people are to the use of shared vehicles. It is more familiar with tech-savvy, younger generations, who also tend to live more often in the inner cities. The familiarity is a variable, which can be influenced with good communication and test offers.

Costs mainly consists of these items:

  1. Depreciation of the investment for the vehicle
  2. Reallocation or redistribution
  3. Charging in case of electric vehicles
  4. Maintenance
  5. Vandalism costs, mainly for bikes and kick scooters
Example for costs and revenues per shared bike and month depending on the distance from the city center – in reference to a supply/demand chart. The intersection of the cost and revenue curves shows the equilibrium up to which distance operations of a shared bike will be profitable and therefore served by bike sharing providers.

The example above shows how typical costs and revenues depending on the distance from the city center under the following assumptions:

  • It is harder to rent out vehicles in the outskirts than in the city center. Therefore the revenues decrease with the distance from the center.
  • The surface area to be served increases as a quadratic function to the distance from the center, i.e. the radius of the area of operations. So the costs for reallocation and service also increase exponentially with the distance from the center.

This explains why shared fleet operators optimize their area of operation and tend to pick the raisins in the city centers.

This screenshot from the former sharing service aggregator CarJump shows the concentration of sharing services in the city center of Berlin. Covering the entire city and the outskirts would require to triple the radius.

Potential Solutions

At the Future Mobility Camp @Home 2020 we discussed what options shared mobility providers and municipalities have in order to extend the area of operation:

  • Subsidies
  • Crowdsourcing of charging and vehicle reallocation
  • Enforcement via operating licenses for entire areas
  • Free floating offers in the city, station-based “satellites” outside
  • Shared service operations among all providers
  • Alternative business models, such as P2P sharing

We will have a closer look at some of these possible solutions:

Subsidies

Public subsidies in return for an extension of the area of operation were a commonly mentioned intervention. If the provision of shared cars, bikes and scooters is seen as a part of the public service infrastructure mandate, it could justify public funding to extend it to areas otherwise not being served.

The chart below shows the effect of a “flat” subsidy per ride. It increases the revenue – but mainly where there are many rides, which is not the case in the outskirts. Therefore the effect such a flat subsidy is rather low.

Depending on the slopes of the revenue and cost curves flat subsidies might not have a substantial effect on extending the profitable distance from the city center

Subsidies could also be funded e.g. by university campuses or business parks outside of the regular area of operation – in return for the extension of the service to their premises or “satellites“. Instead of a subsidy per ride a certain number of rides could be guaranteed, which would motivate the operator of the premises to promote the service.

A generic version of these satellite subsidies would be a subsidy which increases with the distance from the city center. Such a distance-based subsidy would more effective than a flat subsidy per ride.

Subsidies which increase with the distance from the city center (no subsidies in the center, high subsidies in the outskirts) will likely be more effective with a given budget

Crowdsourcing

Another interesting solution discussed was the sourcing of certain tasks to “the crowd”, i.e. to people, who are anyhow close to where the vehicles are and so have lower effort and costs.

This concept is commonly used by kick scooter companies to charge their vehicles with the help of so called “juicers“. These are gig economy workers who collect, charge and sometimes also redistribute the scooters on behalf of the operator and get paid per scooter being charged.

The same concept could also be integrated into the tariffs, so that no “workers” need to be hired but the users of the vehicles take over some duties. A common practice is refueling gas of shared combustion engine cars or charging electric vehicles in return for free mileage.

One of the highest cost factors for shared fleet operations is the reallocation or redistribution of vehicles. Especially bikes and scooters often get rented at subway or train stations but then left somewhere in the city or even outside. Reallocation assures that the vehicles will be available where they are needed the next morning. It is high effort as the vehicles need to be located, collected, checked and then be placed at the areas of the expected highest need.

Rewarding users via incentives to place the vehicles where they are needed could be a smart alternative to the use of dedicated workforce – similar to a deposit. Many bike sharing companies already charge a penalty on top of each ride if the bike is not returned to one of their virtual or physical stations, which usually represent such high demand hot spots. Positive incentives could be given for users who pick up vehicles in low-demand areas and drive them to high-demand areas. This could be discounted rides or even paid rides depending on where the vehicle is located. Overnight tariffs would also be a smart alternative to charging a penalty for leaving the area. With such an overnight tariff users could take the vehicle home at night (which can be way outside of the area of operation) and and bring them back to the area of operation the next morning for a discounted price. This could extend the area of operation even to rural areas at times where alternative means of transport are no longer available – adding high value.

Letting users redistribute the vehicles instead of performing this task with own staff might reduce the overall costs and also flatten the slope of the cost curve

P2P Car or Bike Sharing

An alternative to classic car or bike companies like Zipcar, ShareNow or bike sharing companies Call a Bike or mobike might be peer-to-peer (P2P) sharing companies like Getaround our Turo for cars and Spinlister or List’n Ride for bicycles. These companies do not operate the fleets on their own but instead rely on private owners to rent out their vehicles. So their costs are independent from the location, which explains why these P2P services are often the only available sharing options beyond the city centers. What makes these options unattractive for the daily commute use case is that they are “station-based” by nature. Users can pick up the vehicles at the owner’s location but have to bring it back there. The commute use case would also require to rent it for a whole day, which would both be expensive and also not allow other users to use the vehicle in the meantime. So bottom line P2P vehicle sharing is great for weekends and full-day journeys but not a reasonable option for commuters, where the vehicle would only be needed for just an hour in the morning and in the evening.

Conclusion

In our example a combination of distance-based subsidies and crowdsourcing shows the highest effect and helps to extend the area of operation to reach substantially more citizens. But it is just a specific example and might not hold true with other assumptions.

Combining different interventions could significantly extend the range where shared vehicle fleets could be operated profitably

Each city is different and will lead to different cost and revenue functions. These economies need to be well understood and interventions designed accordingly. We just touched a few of many possible interventions but could already see where they might be beneficial.

We are looking forward to hearing from readers who got experience with similar or other solutions!

Shared Mobility Desert Outside the Cities
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One thought on “Shared Mobility Desert Outside the Cities

  • 2020-06-03 at 17:33
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    I would be curious if the demand would increase over time after people became familiar with and got used to the availability of the shared cars or bikes. Is there any research on it out there?

    Reply

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