Clarifying Questions:

1. Is it an aggregator model using existing bike providers or starting a new one?

2. Are we supposed to optimize the bike sharing for a specific goal? e.g. maximize use of bicycle, acceptable wait time etc?

Top Equation:

# Bicycles required = # people requiring bicycle in peak time / # people served per bicycle at any time with acceptable wait time

Now lets solve this one by one:

1. To solve the first part of the puzzle, we need to make certain assumptions:

Population of a big city 5M

Target users who would use the bicycle sharing

1. Visitors/ travelers (1% * 30% )

2. Daily Commuters taking public transport (10% * 30%)

3. Shoppers (2% * 20%)

4. Students – school/ college (20%*30%)

#2 and #3 would show opposite characteristics over weekdays and weekends. e.g. commuters would be 10% over weekdays but shoppers would be 10% over weekends

# people requiring bicycle per min in peak time = # population require bicycle / peak duration in min

5M*0.01*.3 + 5M*.1*.3 + 5*.02*.2 + 5*.2*.3 = .5M

2. To solve the second part of the puzzle, we need to look at the demand patterns:

Lets say that demand is evenly sparsed in the peak time and the peak duration is between 7-9am in the morning where most commuters and students travel

So peak duration is 2 hrs = 120 mins

Average distance a person can/ will travel on a bicycle = 1 Mi

Average time a person can/ will use a bicycle in peak time = 10 min including traffic time

People a bike can serve per min = 1/10

Acceptable wait time = 2 min (assumption as people may prefer to walk instead of using bike to be in office/ school in time)

People one bike can serve in 120 min = 12

# people served per bicycle at any time with acceptable wait time = 1/5

Now lets feed this into our top equation to get the estimate of bikes required:

# Bicycles required = .5M/.2 = 2.5M

Since we have our estimate at hand, lets double check whether this number seems reasonable.

Bike Required is coming out to be half the size of the population, so we need to go back and correct our assumptions.

Our estimation of the second equation seems correct but the population set requiring bike seems way off.

Couple of additional factors that come to my mind:

1. We have considered the full city population while we could narrow it down to a specific area that we like to target but lets not talk about that for a min

2. Our population number is still the people who prefer to use bicycle for their mode of transportation but we haven’t considered how many of those would be interested in bike sharing service. Lets say this number is 10%

3. Even for the population that is interested in using bike sharing population, our penetration may be slow and lets say we can only take 10% of the market of interested people as there may be other players

So reworking that equation with #2 and #3

# people requiring bicycle per min in peak time = .5M * .1 * .1 = 5K

So revised estimate for # Bicycles required = 5K/.2 = 25K

This number would be reasonable to serve a large city and to penetrate deep into the market. However, company might want to target a smaller area to test their operations out and can actually reduce the bike requirement to an acceptable number.

The number of bicycles required to start a bike-sharing operation in a big city depends on various factors, including the city’s population, geographic size, existing transportation infrastructure, and demand for such services. So, unless you provide some more information it might be difficult to estimate, but here’s a general estimate, but keep in mind that each city’s situation will be unique, and a detailed feasibility study should be conducted for a more accurate assessment:

1. Population and Demand: The first step is to estimate the potential demand for bike-sharing in the city. This could be based on the number of commuters, tourists, or other potential users. Conduct surveys or analyze data from similar cities to get an idea of potential ridership.

2. Coverage Area: Determine the size of the service area. A bigger city may require more bicycles to cover a larger geographic area.

3. Rider Density: Consider the density of potential riders. If the city has a high population density and many commuters, you may need more bikes per square mile.

4. Peak Hours: Identify peak usage hours and days. In busy cities, you might need more bikes to accommodate rush-hour demand.

5. Bike Turnover: Estimate the number of trips a single bike can handle in a day. This depends on factors like the bike’s durability and maintenance.

6. Initial Investment: Calculate the initial investment required for purchasing bikes, docking stations, and setting up the necessary infrastructure. This can be a significant cost.

7. Maintenance and Operating Costs: Consider ongoing maintenance and operational costs. This includes repairing and maintaining the bikes, as well as marketing and customer support.

8. Scaling Over Time: You might start with a smaller fleet and expand based on demand. It’s often more practical to start with a manageable number of bikes and increase the fleet as you gain experience.

9. Regulations and Permits: Be aware of any regulations and permits required for operating a bike-sharing service in the city. Compliance can affect your initial setup and ongoing costs.

10. Competition: If there are existing bike-sharing services in the city, you’ll need to assess how you can compete with them. You might need a larger fleet to attract users.

11. Technology and App Development: Consider the cost of developing a mobile app for users to locate and rent bikes. This is a critical part of modern bike-sharing services.

12. Sustainability: Depending on your city’s environmental goals, you might aim to have a larger fleet of electric or hybrid bikes, which can be more expensive but attract eco-conscious riders.

After gathering all this data, you can create a financial model to estimate the number of bicycles required. Generally, a typical bike-sharing service in a big city may start with several hundred to a few thousand bikes. However, in extremely large cities, this number could be much higher. It’s essential to work with experts in urban planning, transportation, and finance to conduct a thorough feasibility study and make a well-informed decision regarding the initial fleet size.

Let’s assume the population of a large city is 10million. Given ride sharing is suitable for more dense areas, I want to first offer it to the people in busy neighbourhoods (i.e. downtown). Let’s assume 30% of the population lives in downtown. The estimated population of people in downtown would be 3 million.

Now, lets assume the 3 million people have an even age distribution from 0 to 80, meaning there are 3million / 80 = 37.5K people per age year.

There are two groups of people who will use a bike:
– those who use bicycles for commute to work (school) + other things
– those who use bicycles for everything other than commute to work

First, let’s look at population of people who are willing to use bike to commute to work + other things.

Say the target market is in age range of 15 to 45 with the following probability of interested in using bicycles as one method of transportation to work(school) + other things:

age group 15 to 20 – 5% interested in using a bicycle as method of transportation for work(school) + others —> estimated population 5×37.5Kx5%= around 10K
age group 20 to 30 – 10% interested in using a bicycle as method of transportation for work (school) + others—> estimated population 10×37.5Kx10%= 37.5K rounded
age group 30 to 45 – 5% interested in using a bicycle as method of transportation–> estimated population 15×37.5Kx5%= around 30K

Total target bikers population in downtown = 10K + 37.5K + 30K = around 80K

Let’s assume 30% of these people are willing to use bike sharing and 70% prefer to continue using their own bikes. Now, the total number of people willing to use bike sharing for commute to work (Schoo) + other things is 30% x 80K = 24K

Now, if these people use the bike 2 times per week day (it might be slightly higher since they use the bike for shopping too but then they also go on vacation so let’s say 2 per day), they will have 2 x 24K = 48K rides per day. Assume each ride takes 15 minutes, this group does 48K x 0.25 hour = 12K hours of bike ride per day

Now to calculate total number of people in group 2,

First, let’s get an estimate on the total number of people willing to use bicicyle for going shopping / travelling to friend’s place, etc. Let’s estimate the population of this group in our target age range (15 to 45):

age group 15 to 20 – 20% interested in using a bicycle as method of transportation –> estimated population 5×37.5Kx20%= 37.5K
age group 20 to 30 – 30% interested in using a bicycle as method of transportation–> estimated population 10×37.5Kx30%= 112.5K
age group 30 to 45 – 20% interested in using a bicycle as method of transportation–> estimated population 15×37.5Kx20%= 112.5K

Total = 37.5K +112.5K + 112.5K = 267.5K

Let’s also assume 30% of these people are willing to use bike sharing and 70% prefer to continue using their own bikes. Now, the total number of people willing to use bike sharing in group 2 is 30% x 267.5K = 90K

About 24K of people in this group belongs to group 1. In other words, people who use their bike for transportation and not commute to work is 90K – 24K = 66K.

Say say these people use the bike about 1 time per day to do a transportation for 15 min. That would mean they do about 66K x 1 x 0.25 hour = 16.5K hours of transportation per day with bike

So, total estimated bike ride time per day is 12K + 16.5K = 28.5K hour per day.

Assuming that during first 2 months of the bike share launch, company can obtain 10% of target market, it will need to be able to support 10% of 28.5K = around 3K hour of bike ride per day.

If we want each bike to have a utilization of 50% to make sure that there are always some bikes available in the bike share stations and if each bike is used from 8am to 12am evenly during the day (this is a big assumption given many people go to work or school to be in their office or class at 9am), we can say that at 50% utilization for 16 hours a day (time from 8am to 12am), each bike can ride for 50% x 16 hours = 8 hours per day.

Now, divide the 3K hours by 8hours and you get the minimum number of bikes needed to start the company. 3K divided by 8 equals 375.

Another method to calculate this number would be to estimate number of bikes needed to support the bike share members at the busiest time of the day (it’s most likely from 8 to 9). Let’s say that at this time, 50% of the 90K bike share commuters go to work (school). This means the bike share company should be able to support 90K x 50% = 45K bike rides during 8am to 9am time interval. Assuming each ride takes 15 minutes, 45K bike rides translates to 45K x 0.25 = 11.2K hour of bike ride. Let’s say the company needs to be able to have infrastructure to support for 10% of the these rides during first two months of operation, meaning 11.2Kx10% =1.1K hour of bike ride. Assuming bikes are used at 100% utilization, the company needs to have 1.1K bikes at the start of the bike share program.