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E-bike Sharing

Delivering New Growth for Bike Share Schemes with E-Bikes

Electric bikes (e-bikes) have huge potential for Bike Share Schemes but it brings a new level of management challenges for operators. Over its manual counterpart, e-bikes need to be fully charged for each rider, every time and that requires efficient distribution.

 

E-bike is a pedal bicycle with an electric motor. It assists the rider with additional electric power whilst offering many of the same characteristics as traditional bicycles. Many e-bikes are legally classified as bicycles and subject to the same local laws.

 

E-bikes can be a great way to travel. It can reduce door-to-door time of commutes with a lot less effort and makes transport more accessible to the new or less-experienced cyclists. For operators, it delivers new opportunities to compete in the industry and win new riders.

 

In the recent CES 2018 event, we saw many operators reveal their plans to incorporate e-bikes. Limebike, Spin, Ford GoBikes and Social Bikes all announced the introduction of e-bikes within their operations. It marks the shift in the industry that caters to the end users and their Bike Sharing experience.

 

E-bikes are a convenient way to get from A to B but it is faced with challenges in the market that limit its growth. The perception of e-bikes as ‘cheating’, the added weight of the battery pack to cycles and the cost of purchasing and repairing one all affect e-bike adoption with the public.

 

Manual pedal bikes are also much cheaper and easier to purchase, build and maintain for operators. It makes it simple for operators to grow fast and grow far. It’s one of the reasons why we are seeing thousands of pedal bikes being launched globally and at such a rapid pace.

 

For operators, the key is to deliver a service that people will want to use regularly and e-bikes offer a solution that removes the limit on how and when riders can use the schemes.

 

One major concern I see is in how operators manage their e-bike schemes. The demand for e-bikes is likely to be higher than the current pedal Bike Sharing schemes. It will put pressure on operators to deliver each and every time.

 

E-bikes will also need to be charged at the end of the trip and ready to be used by the next rider. That requires seamless management of resources and expert understanding of the local market.

 

Bike Share operators will need to have a strong management process in place to not only handle the challenges of e-bike sharing but to also take full advantage of the many opportunities it looks to bring for operators. Operators will be required to match local demand with efficient redistribution to succeed in the market.

 

At Stage Intelligence, we are using our expertise in Bike Share management to address the challenges of e-bike sharing. We are incorporating new e-bike technology within the artificial intelligence platform. Our processes enable us to add new features and functionality to cater to the dynamic Bike Share market.

 

To find out more about how Stage Intelligence can support and simplify your Bike Share Scheme operations, please contact tom.nutley(@)stageintelligence.co.uk

Increasing Rider Satisfaction with Artificial Intelligence

Big data and Artificial Intelligence (AI) provide a valuable opportunity for growth to Bike Share Schemes that have been deployed and developed across the six continents. Both schemes that are in the planning stages and ones that have already been deployed can benefit from leveraging big data and AI

Operators looking to drive growth to their schemes need AI to sort through vast amounts of data. If you combine millions of different criteria across a large urban area, the sheer number of possibilities can be overwhelming.

Every element matters and can influence where bikes are dropped and congestion occurs. In the worst-case scenarios, a rider borrows a bike but can’t find a dock and must travel away from their destination to drop it off and when they return there are no bikes remaining.

Data and AI is key to avoiding this situation. It ensures rider satisfaction by predicting demand in popular areas and managing supply. Only with data and AI technology can Bike Share Schemes look to improve existing processes, operations and logistics, and drive growth to their operations.

Going forward, data needs to be more accessible to operators. Open data allows Bike Share Scheme operators to deliver a transport solution that works for all. Data ensures bikes are available when and where it’s needed to support the growth of Bike Share Scheme deployments around the world.

Regulations such as the General Data Protection Regulation (GDPR) will still be paramount in the push for the openness of data. Cities, operators and all others involved have a duty to follow secure practices and take necessary steps in protecting user information.

Data and AI are ready to help operators to adapt and grow their schemes while refining and simplifying how they manage distribution.

For operators, getting started is simple:

  1. Evaluate long and short-term goals and growth objectives
  2. Explore what AI-based management platforms are available
  3. Look at what open data, shared data and Smart City initiative have been launched or are being developed locally
  4. Collaborate with AI experts and begin the journey towards smarter and more efficient Bike Share Schemes

To find out more about how operators can grow their Bike Share Schemes, read our full whitepaper on ‘How to Grow a Smart City Bike Share Scheme’.

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’

 

7 Benefits of an AI-Optimised Bike Share Scheme for Smart Cities

Smart Cities that have active and growing Bike Share Schemes create urban environments that are healthier, with less congestion and better placed to manage growing populations.

In 2016, 1.7 billion people or 23% of the world’s population lived in a city with at least 1 million inhabitants, according to the United Nations. By 2030, that will grow to 27%. Urbanisation is continuing to grow and that puts strain on transportation networks.

Public Transport in its current state is already stretched and cities are often challenged to fund new projects. With optimised Bike Share Schemes, cities can encourage citizens to cycle and avoid crowded transport systems.

As more Smart City initiatives are deployed, cities become data-rich environments that can benefit Bike Share Schemes. The emergence of the Internet of Things (IoT) and a growing number of connected devices deployed across a city will only expand the potential of Artificial Intelligence (AI) in Bike Share Schemes and transportation overall.

Expanding data sets managed with AI can deliver results that directly benefit riders and influence how a city functions and grows.

All cities can benefit from an AI-driven Bike Share Scheme but as smart technologies are rolled out widely, the depth of data will grow. Operators benefit from new and increasingly precise insights while riders will see Bike Share Schemes optimised in new ways.

With AI, operators can ensure a well-run Bike Share Scheme that offers:

 

A Cleaner Transport Option:

For cities to help tackle climate change and deliver a better environment for citizens to live in

 

Healthier and Happier Riders:

Through daily exercise

 

Effective First & Last Mile Solution:

Since it can be significantly cheaper and faster than other public transport options for short distances

 

Reduced Strain on Infrastructure:

As less people are using public transport that requires continuous upkeep and maintenance

 

More Investment in Cities:

With less need for maintenance and new projects, Smart Cities can use funding on other much needed transport infrastructure such as cycling lanes and incentives

 

Manage Rising Transport Demand:

With increasing urban-dwellers, cities can offer more transport options with a Bike Share Scheme to accommodate this rise

 

City’s Brand Image:

Can be shaped by a cycling culture, supporting tourism and other thriving economic industries

 

Bike Share Schemes are like no other modes of transport. It offers a viable transportation option to many crowded cities that deliver a range of benefits to both cities and its citizens.

To find out more about the benefits of Bike Share Schemes to operators, cities and citizens, read our full white paper on ‘How to Grow a Smart City Bike Share Scheme’.

How to Grow a Smart City Bike Share Scheme

Smart Cities offer an entire ecosystem of valuable and relevant data that Bike Share Scheme operators can use. Smart City data can be used to identify trends and provide actionable insights that can drive the growth of Bike Share Schemes.

These four questions about data hold key information that Bike Share Scheme operators can use to reshape their approach:

  • Who are they?
  • What is happening in the City?
  • Where are they going?
  • What are they saying?

Bike Share Scheme operators need to know not only who their riders are but also the potential of the market. Citywide census and records collect data on population and demographics as well as human behaviour that can be used to predict the future of such schemes for operators. Trends in demographics can be identifiers for areas of growth in specific markets.

Cities also offer the potential to track a range of real-time data from traffic to weather and major events. Understanding how areas are being used at different times of day, by different types of people, and in response to different events through real-time data, can be highly beneficial to operators. A dynamic scheme is the first step in providing mobility options that work for all.

How people move in urban cities is just as important as identifying who they are. Fortunately, cities have a way of capturing this data too. Mobile phones, parking sensors, congestion zones all yield data about how and when people are moving around the city. Transport for London (TFL), a body responsible for the cities transport system, can track passenger movements through the Oyster card. For Bike Share Scheme operators, this data allows them to provide resources that are better attuned to the rider’s needs.

In a more connected and social world, it is also much easier to find out what people are thinking.
As an example, sentiment analysis can be used to track attitudes and opinions on social media. Operators can use this data to see how people react, what they like and dislike as well identify any opportunities for improvement. Ridership is the key to success for Bike Share Schemes and insights on this data can go a long way in ensuring the satisfaction of riders.

The challenge for operators is in how this data is collected and managed. Smart Artificial Intelligence (AI) systems will make use of public data feeds and encrypt user information to ensure the security of data.

For Bike Share Schemes and other transportation networks, it is imperative that they comply with existing and soon-to-be implemented regulations on data collection, privacy and usage such as the General Data Protection Regulation (GDPR). The EU GDPR replaces the Data Protection Directive 95/46/EC and was designed to harmonise data privacy laws across Europe, to protect and empower citizens and to reshape the way organisations approach data privacy.

To find out more about what data is available in Smart Cities, read our full white paper on ‘How to Grow a Smart City Bike Share Scheme’.