When you turn off your alarm on your smartphone at 6:30 in the morning, it is straightaway clear that it is a better plan to work from home this morning instead of at the office. There are traffic jams everywhere and even the trains are delayed. It is advised that you leave two hours later instead. In case you do not want to follow this advice, because you have a meeting at 9:00 in the morning, then your smartphone gives the fastest route straightaway, considering going by car or by public transport. Later that day, you have to be at the dentist at a specific time, whereby your smartphone notifies you when you have to get in your car.
People get busier every day and the personal and digital demands are increasing. Systems get integrated more and more, which leads to an optimal ease of use. Those trends can be applied on the travel and traffic industry too. A lot of problem solving traffic applications have been developed, which led to an online overload (Tsekouras, 2015) of applications that can help you on the road. In this blog I provide you with the mechanisms in those traffic applications, and I will provide an analysis of the different applications which are currently popular in the Dutch market.
Travel & Traffic Applications
The aim of travel & traffic applications is to give and advice about how to get from A to B fastest. Nowadays, a lot more functions are possible such as a personal navigation (to avoid traffic jams), a price advice, a sustainable advice etc. To optimize and customize this for each individual, the user needs to put in information in exchange. With this, the users deliver an input for the actual result.
Since everyone has different destinations, different travel times, a different budget, and different resources, those traffic applications cannot give a generic travel advice to everyone. The key point of those applications is that travel advices are based on personal data, such as one’s car, one’s agenda, the amount of traffic jams on the highway, and one’s preferred budget. With this, everyone receives an optimal, personal travel advice. Since the user types in the data him/herself, optimal advices are given, instead of a ‘guess’ based on the most likely information. The downside of typing in one’s exact data is that it requires effort, whereas minimal effort is desired. To lower the impact of this downside, most applications can be fully integrated with one’s smartphone and agenda, which decreases effort in turn. However, this raised privacy concerns at the same time (Tsekouras, 2015).
There are endless possibilities that can be integrated in traffic applications. Most traffic applications integrate the following elements:
- Real-time traffic notifications
- Personal schedule
- Prices (of fuel or public transport)
- Available parking spots
- CO2 saving
- The amount of stop overs
Most applications have different revenue models, varying from paying for the download to advertisement based. Noteworthy is the fact that a lot of applications are run by the government and some applications are highly subsidized due to the benefit for the whole community.
In the following table, an analysis of popular traffic applications in the Dutch market is given.
Tsekouras, D. (2015). Lecture 1: Introduction to Value Co-Creation. Customer Centric Digital Commerce, 18 March, 2015.
Tsekouras, D. (2015). Lecture 2: Information Search & Product Recommendations. Customer Centric Digital Commerce, 25 March, 2015