Exploring Business Models for Integrated Urban Mobility

Exploring business models for integrated urban mobility

With my knowledge and experience building an operating cost model for a ridesharing platform. I see important elements that need to be clarified going forward.

The first is to do with the influence of distance on the pricing model. The collector distance is calculated simplistically in our current approach. If we are presented with large sample size, how do we accurately determine the appropriate cluster size and resource allocation automatically, instantly? That is the current bone of contention which has been explored by (reference material related to demand responsive a ride-matching/sharing technologies). Granted from the results of the current model we see that it is not worthwhile for an individual to invest in a platform that exceeds their current monthly expenses. That is to say, there is not enough disposable income, to warrant the success of the current operating model. Moreso a dialogue with a few of the operators seems to paint a picture of bargaining it is thus important for us to approach with an appreciation of the genuine costs behind the business to ensure success. We see ourselves faced with the same challenge as we enter Hertfordshire. There is a striking resemblance in the product that we want to offer. To understand one crucial factor is the realisation of a demand-responsive service. That is the main objective. With Hertfordshire we have a positive inclination towards the use of public transport, however, a report objected to this. Granted there is always a negative perception around public transport, with Hertfordshire the current utilisation levels of the public transport infrastructure favours our product more. The idea is to promote access to public transport systems as they are the backbone of any urban mobility endeavour.

Promoting access is achieved through the integration of complementary transport services to reduce traffic volumes. With Hertfordshire, the argument should be how do we increase and improve current capacity. We are therefore entering the market with a smart transport solution connecting economical active individuals to centres of employment. What is important to stress here going on is that for the county to buy into this vision they need to see tangible effects on the existing systems, that is to say, improvement and well utilised public transport facilities and this can only be achieved by looking at integrating the local public transport modes onto the platform.

What business model do I see out of this? We are in between an engineering consultancy and a county authority both willing to engage with our technology to solve its problems and plan for the future. What is valuable to us is data. As an integrator, our ability to provide and acquire data will determine the success with which we penetrate the market. In understanding that data is our value we then seek to explore what scenarios can emerge that will still leave us with control over the most valuable resource. Here we start looking at the architecture of the technology that we want to present to the county. What must be supported by this architecture, where the end goal is to deliver a platform for managing and delivering transport data through various integration techniques that we would have accumulated in-house.

We want to connect individuals with similar travel needs. With this, we improve the utilisation of existing transport infrastructure. Instead of five people located in proximity to each having to drive to the same working area, they share a ride and reduce the number of vehicles that would have otherwise been on the road had they chosen to use their own cars. The importance of connecting to public transport shows us that for people that may otherwise have different travel patterns in the return journey, there needs to be an alternative for them to meet their transport needs. Here we explore connecting to other transport operators to explicitly state our role as an integrator. I see myself using a reliable public transport system that is responsive to my real-time demands as I walk out of the transit station. That is to say outside the core mass public transport services which will likely be a train, how do we connect that service to an external provider like UBER and FLX to deliver intermittent transport journeys between inaccessible areas of the city, which would have otherwise prompted car use. That is solving the first-mile last-mile problem. Fulfilling the gaps that are left out by current public transport routes. That way you optimise infrastructure use.

Now, as I engage further with understanding the various business models, I would like to briefly explore the different approaches and methodologies that have been used to develop a demand-responsive solution. Here is to understand the languages and techniques that have been employed and are currently being employed in achieving a real-time demand responsive transport system.

So what business model will work for the successful application of a demand responsive service in developed and developing markets?

We see the distinction that exists in these markets based on the sophistication of the virtual and physical infrastructure supporting transport provision. Common themes in the dialogue, however, speak to increased population growth and a rapid increase in congestion which has had an effect on increasing journey times. With this distinction in mind, I would like to closely borrow some epimostological evidence from the current knowledge I have of public transport systems in emerging markets and use this to form the basis of a pseudo universal solution that seeks to see the movement of people as a global challenge.

In a utopia, I could argue how much of the informal transport in emerging markets is demand-responsive. With this, I set the question forward of what makes a system demand-responsive or rather what defines a demand-responsive transport system outside the confines of technology. The emergence of informal transport services is a response to demand. With this, I would like to explore the complexity in transport systems in emerging economies and present those and potential solutions to address the imminent and current challenges facing many European cities at the moment with regards to the last mile first-mile problem.

What city mapper did was simply put a tablet and sophisticated equipment in your usual low-quality public transport service in emerging economies. Here I argue that the technology required to address this challenge is universal that is the activities of this business endeavour without much alteration allows the development of a universal technology stack that can solve and respond to transport demand in real-time.

Real-time means the ability to co-create the core elements of the system required to support the public transport network. What differs perhaps is the value proposition.

For us, we would rather ask, what is the cost of placing tablets in minibus taxis and deploying them into the public. That is the question of the emerging market, to first understand the current system and see how technology can improve the service of these already demand responsive transport services. How do we embark on a modernisation programme of our existing public transport service and this is not to invite tendeprenurial thinking. We measure and analyse the exisiting capacity of our public transport system and see how we can aggregate and improve capacity utilisation based on informed data and evidence-driven processes.

For developed markets, the next question is how do we export this knowledge to solve the last mile first-mile challenge of the European city. ?

I trust that with this question I have made myself clear in terms of how I would want the technology of demand responsive transport to be developed.

There is knowledge in Africas informal economy