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Bike Sharing and Micro-Mobility Shifted Gears in 2018

2018 was the year where Bike Sharing and Micro-Mobility showed its potential to change urban spaces and the transportation industry as a whole. Docked or dockless Bikes, e-Bikes, scooters, e-scooters and a whole range of new mobility options have become the most exciting and innovative sector in transportation.

 

If we go back 15 years, there were just four Bike Sharing Schemes. In 2018, there were more than 1,600 globally, according to Bike Sharing consultancy MetroBike. These schemes account for 18.2 million public-use bikes available around the world, nearly double the number from four years ago.

 

Growth is expected to remain in double digits for the next eight years at least. Research and Markets expects global Bike-Sharing market to grow at a Compound Annual Growth Rate (CAGR) of 12.5% between 2018 and 2026.

 

At the same time, schemes are diversifying and going beyond traditional Bike Share models. In the spring of 2018, multiple US cities started facilitating electric scooter services, which lead to 3.6% of people claiming to use the sharing-scheme. An impressive statistic, considering the market was only made available to the public less than 12 months previously.

 

Inside a Populus report – The Micro-Mobility Revolution – they highlighted that 70% of their respondents viewed electric scooters as a positive addition to urban areas – predominantly as they’re more convenient for shorter journeys, compliment public transport and extend their choices of transport as a whole.

 

In April, we saw the beginning of convergence between mobility platforms with Uber’s acquisition of Jump Bikes in April. Uber signalled it would be adding additional ways to move around your city directly from the Uber app. It has recognised the value of micro-mobility to its future and is prepared to spend capital and resource to get in the game.

 

The market is changing fast and that’s exciting but it hasn’t all been good news.

 

In China, a dockless Bike Sharing system was launched that charged cyclists just pennies for a half-an-hour ride. However, the initiative out-grew its demand, meaning there were too many bikes and not enough riders. The bikes were dumped –  in the streets, sometimes in rivers – and that lead to them being laid to rest in ‘bike cemeteries”.

 

In May 2018, the city of San Francisco temporarily banned electric scooters after residents complained of congested streets and illegal parking. The city received 1,900 complaints about the new vehicles. In August, San Francisco Municipal Transportation Agency announced Scoot and Skip as the winners of its e-scooter pilot sweepstakes, bringing e-scooters back to the city.

 

Across the Micro-Mobility industry, growth is being matched with experimentation and a healthy skepticism from local authorities. As in any rapidly evolving market, we are going to see more successes and failures in the next 12 months with efficient and consistent scheme management being a common challenge. No matter what type of scheme is being operated, end users need an optimised experience and operators need an efficient way to manage them.

 

As the market grows in complexity, Stage Intelligence uses its BICO AI optimisation platform to solve these challenges and simplify how schemes are managed. As our industry goes to a new level, we’re taking scheme management to new places with Artificial Intelligence.

 

Please get in touch if you’d like to know more about how we can help you get the most out of your Bike Sharing Scheme:  info@stageintelligence.co.uk

Using Autonomous Vehicles To Manage Bike Share Schemes of the Future

While fully autonomous cars are still years away from being a mode of transportation that we can use day-to-day. We think it could have a positive impact on Bike Share Scheme management in the future.

 

With 68% of the world population projected to live in urban areas by 2050, we believe the future of mobility lies in simpler, cleaner and space saving modes of transportation like walking or cycling. Autonomous cars could play a big part in this.

 

In Bike Share Schemes, driverless cars could open up new opportunities in optimising management to deliver a better scheme to its riders. It can make the redistribution of bikes in the future much easier and more cost-efficient for the operator. Data, Artificial Intelligence (AI) and autonomous technology can all interlink to carry out traditional operational processes.

 

Currently, operators have to rely on manual processes for redistribution with trucks and vehicles being led by operational staff. That requires a significant amount of internal planning on where the drivers need to be, at what time and taking into account shift breaks and patterns.

 

Fortunately, Bike Share operators now have a lot of tools and technology at their fingertips that can help optimise and manage this. AI-based management platforms are helping operators with a lot of the heavy lifting and giving operators the most optimum way to manage operational staff.

 

In a future where driverless cars are commonplace, we can see Bike Share Scheme management moving towards the use of this technology. It has the potential to directly connect with management platforms to optimise how the redistribution trucks move, where they go and how often they go there. That can all be done with minimal human interaction.

 

For Bike Share Scheme operators this can remove the limits on rebalancing its bikes and offer a better and more reliable scheme to its riders. When Bike Share Schemes are better managed, operators can reduce costs and accelerate rider experience.

 

You are able to accurately serve the local market and ensure bikes are available when and where it’s needed. That supports the move towards shared integrated transportation and gets more people cycling.

 

Autonomous cars have a lot of potential for Bike Share Schemes and wider transportation in general, but it is still very far away from reality. At Stage, we’re always looking at the future and seeing how complex challenges of today could be solved by the technologies of tomorrow.

 

We’re excited to see what new technology will bring to the growing shared mobility market and how we can best incorporate it to deliver smarter processes to the wider industry.

 

Please get in touch if you’d like to know more about how we support Bike Share operators with a simplified management processes: tom.nutley(@)stageintelligence.co.uk

 

 

4 Reasons Why Scheduled Bike Share Redistribution Doesn’t Work

The biggest challenge in Bike Share Schemes is to provide an optimised service each and every time. Operators that choose schedule-based distribution are often limited in their rebalancing efforts and are not efficiently serving the local rider demand. That impacts ridership and rider experience as a whole.

It’s up to the operators to ensure they have a simple and optimised management process that’s tailored to the cities and the riders. It enables them to offer better services, build stronger ridership and reduce operational costs. Yet many operators still choose to carry out schedule-based redistribution.

Schedule-based distribution means drivers have pre-set information or a schedule of how many bikes to pick-up and drop-off and at what locations. The schedule is created irrespective of the city it’s operating in or its specific needs. This can often mean that by the time the first job is completed the whole schedule could be wrong.

Poor rebalancing and management processes can also add to the growing situation of bikes being left as a nuisance to cities and its citizens. Singapore has seen first-hand the impact of poorly managed resources that have a huge effect on the day-to-day lives of its residents.

To combat indiscriminate bike parking, The Land Transport Authority (LTA) in Singapore passed a legislation earlier this year aimed at tackling this issue for over 100,000 bikes in the area. Since then it has introduced several new measures including reduced fleet size and Bike Share licences to ensure operators are better managing their schemes.

It is now more important than ever to have a smart management process that takes the guess work away from Bike Share redistribution.

Here’s four reasons why schedule-based redistribution doesn’t work for modern Bike Share Schemes:

 

  1. Dynamic Nature of the City

Cities globally are different from one another. They all have different population, city topography, transport hubs and many other factors that make each and every city unique. A schedule that works well in one city could completely fail in another.

  1. Each Day is Different

The day itself plays a huge role in Bike Share ridership. When you combine the changing weather, major city events, transport strikes and a number of other things, the demand for Bike Share Schemes are likely to fluctuate on a daily basis.

  1. Evolving Rider Behaviour

Some riders may take a bike out every morning and every evening to commute between work and home. That makes it predictable and easy to manage. In reality, for many riders their behaviour is constantly changing. Increase in tourists or a rise in public transportation services could affect the demand for bikes in different areas.

  1. Inefficient Use of Staff

What we see every day with schedule-based distribution is that drivers are going from one location to another with no real insights. They often go to a docking station that is expected to be empty and find that it is full. This is huge waste of time, money and resources.

For modern Bike Share Schemes, scheduled-based redistribution doesn’t work. There are too many variables that make schedule-based redistribution time-consuming and inefficient. Operators instead need simpler and smarter processes that can predict demand and manage resources with accuracy.

At Stage Intelligence, we use four weeks of prior ridership data to track rider behaviour and mange redistribution effectively. We predict replenishment values up to 12 hours in advance to enable operators to make quick decision and move quickly to win new riders.

Please get in touch if you’d like to find out how we use data and AI to transform Bike Share redistribution: tom.nutley(@)stageintelligence.co.uk

Delivering On-demand Team Management to Bike Share Operators

Bike Share operators around the world are looking for easier and better ways to manage its operations and operational staff. They need solutions that can make internal team management simple and reliable.

Today, Bike Share operators are struggling with outdated team creation and management processes that restrict how they carry out their day-to-day tasks. They are burdened with manual inputting, time implications and constant miscommunications internally.

When your operational staff are not working together efficiently, your whole scheme could be at risk. Your redistribution and internal operations are not optimised and that could have a negative impact for your riders.

It’s why team management has been a big priority for us. Operators are looking for easier ways for its distribution teams to work together, communicate and collaborate. In BICO version 15.1.0, we made it simple to create and manage multiple teams.

Operational staff can now set up teams in real-time without the need to do so in advance. They are free to start their day and update the app as they pick up new job requests. It saves valuable time and effort for staff and enables them to operate more efficiently when redistributing the bikes.

Bike Share operators really benefit from a dynamic management platform that can keep up with the changing industry. You’ll see better optimised internal processes that enable your teams to work together to better serve the market. That gives riders complete confidence in your scheme.

Riders can trust that your bikes and resources are available when and where they need them. They can rely on your scheme to get to their end location each and every time. That builds strong ridership and helps you grow locally and around the globe.

In BICO v15.1.0, we’ve worked closely with our partners to add new features including:

 

  • Simple Team Creation

Our BICO Android application lets users create teams with the app by selecting a User Name, Shift, Break Time, Vehicle, Depot and Team Name, which can be easily edited.

 

  • User Verification

The latest BICO update includes a simple user verification process that can be set up by entering the username and password. This is an optional feature and can be turned on or off.

 

  • Usability & Stability Improvements

BICO 15.1.0 also comes with a range of usability improvements, general bug fixes and stability improvements.

 

At Stage Intelligence, we’re continually updating our app to deliver a simpler, faster and better way to manage a Bike Share Scheme. We’re improving the usability, stability and performance of the app while adding new features to give partners around the globe a reliable Artificial Intelligence (AI) platform.

 

If you’d like to find out more about the latest BICO update and how that impacts Bike Share operators around the globe, please get in touch: tom.nutley(@)stageintelligence.co.uk

Solving Distribution Challenges in Bike Share Schemes

Effective distribution, in some of the best Bike Share Schemes, require immense amounts of citywide data to be captured, processed and used. Increasingly, schemes around the world are using city data to not only optimise its redistribution but to also show complete visibility to its users as to where the bikes are on its system map.

It’s how Bike Share Schemes use this data that drives value for operators, riders and cities. Bike Share Scheme operators are often familiar with rider statistics and patterns but the challenge is to use this data to accelerate growth within a scheme.

Tracking growth and stimulating growth are often two very different things. At the heart of new growth is rider experience. Bike Share Schemes are challenged to offer a consistent rider experience across a city while ensuring that using a Bike Share Scheme is easy, convenient and enjoyable for the rider. A positive and consistent Bike Share Scheme begins and ends with two questions:

 

  1. “Can I get a bike where I want one?”
  2. “Can I dock my bike at the end of my journey?”

 

If a Bike Share Scheme can guarantee these two things, it is likely that a rider will have a positive riding experience. When a rider can borrow a bike and dock it, they are more likely to use the scheme again and make it part of their routine.

That’s good for the Bike Share Scheme as it will help to grow overall ridership and new people will experience the city using shared bikes. A Bike Share Scheme with an active and growing ridership is able to invest and expand its schemes.

The data available in a city can be used to ensure that riders can access bikes and docks where and when they want them. Different days of the week, weather, events, seasons, local conditions and scenarios, and a whole range of criteria can shape how a Bike Share Scheme is used.

On a rare rainy day in Los Angeles, people may not cycle at all. In Amsterdam, there may only be a slight variance in usage patterns. At the same time, different events can be connected like a sunny day in a city, matched with a train drivers strike and major sporting event being held in one area of the city. All of these factors can influence how a scheme is functioning and where more or less bikes are needed.

Artificial Intelligence (AI) can be an excellent tool for simplifying Bike Share Scheme operations while using the power of data to drive decision making. AI can process a variety of data both historically and in real-time
to deliver actionable insights for Bike Share Scheme operators. Operators gain visibility into all of the criteria shaping a cityscape and benefit from useful insights to optimise bike distribution to match changing conditions.

AI accelerates how decisions are made by operators while taking the guess work out of bike distribution. The AI technology can predict peak times up to 12 hours in advance, enabling operators to manage supply and meet requirements in those areas. This ultimately leads to bikes and docks being available and riders getting a better Bike Share experience.

 

To find out more about the role data and AI has on a Bike Share Scheme, read our full whitepaper on ‘How to Grow a Smart City Bike Share Scheme’