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The bicycle, a true icon for the Dutch. And with 22,5 million bikes (that’s aroung 1,3 p.p.) we’ve well outperformed Katie Melua’s hit song of 2005 . When these amounts in mind it isn’t strange that we’ve seen several new business models trying to capture value from the Dutch’s cycling habit.

 

One of the most dominant business models (in multiple ways, as I will discuss) is the model of sharing bikes. The bike sharing business model knows two forms: station based and free floating. The station based model obliges its users to pick up and drop off the bike at specific service points, where the free floating enables its users to drop off a bike at any random spot (often through the use of IT). ‘OV-fietsen’ are an example of a successful station based iniative. On the other hand, the introduction of oBike in Rotterdam (and Amsterdam before that) has turned the enthusiasm it was initially received with into a lot of negative publicity.

 

The main convenience of free floating business models, like oBike, is that you can drop off your bike at any point. So that is exactly what people do. Leading to hordes of bikes that are abandoned on the most inconvenient public places. This turns the utopian idea of a ‘green-city’ towards a dystopian reality of a city flooded with abandoned bikes.

Farfetched as this may seem, this dystopia has already become a reality in Katie Melua’s beloved city Beijing. City government has put a ban on new initiatives in Beijing due to the chaos caused by abandoned bikes.

 

In order to protect their investments, companies like oBike are trying to regulate the drop off sites through geofencing. A technique that prevents users from locking their bike at specific places (like Rotterdam Central Station). As customers will be paying until the moment they lock their bike, they are expected to park their bike in a zone that is still available.

Currently, bike sharing companies are experimenting whether this solves the issues adequately hoping for city governments not to proceed with their intent to completely abandon these initiatives.

 

However, geofencing narrows the distinction between station based and free floating business models. As the value proposition of free floating business models comes primarily from the freedom and convenience it offers, and much of this is taken away as geofencing will be increasingly applied, the question is whether free floating models will still be competitive in the future.

 

https://www.nrc.nl/nieuws/2017/09/29/wie-wordt-de-google-van-de-deelfietsen-13258177-a1575451

 

http://bovagrai.info/tweewieler/2016/1-6-fietsenpark-schatting/

 

http://www.bbc.com/news/business-41197341

 

https://www.thebeijinger.com/blog/2017/04/25/beijing-take-action-bike-sharing-chaos-new-regulations

 

https://www.rtlz.nl/algemeen/binnenland/amsterdam-gaat-deelfietsen-ruimen-grote-kans-dat-we-failliet-gaan

 

https://www.nytimes.com/2017/09/02/world/asia/china-beijing-dockless-bike-share.html

 

 

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As you’re reading this blog, you’ve probably heard loads about the emergence of data-driven marketing. A development that prides many companies by enabling them to meet customer demand in the most satisfying way possible. But it’s not just businesses that make use of big data and other innovations to influence people’s behaviour. Although it might be less visible – for a reason – data-driven strategies combined with other technological innovations have dominated the field of electoral marketing in politics.

While electoral marketing has always been data-driven to some extent – primarily demographics and geographics – big data analytics has opened the door to the extremes: psychographics. Where once large surveys were needed to determine and categorize our personalities we are now consciously and unconsciously producing these data around the clock.
Last year’s political highlights – Brexit and Trump – have both put this to use. Big data analysis enabled them to show the right message to the right individual in a uniquely personalized fashion. The CEO of the company hired in both political campaigns to perform these analytics even claims that each and every queer Tweet by Trump was in fact data-driven.

In addition, AI’s are becoming increasingly fast and intelligent in creating realistic content. These AI’s, just like big data-analytics, were used in the Brexit campaign. In this campaign swarms of bots were put to the task of creating and distributing misinformation and fake news in order to manipulate public opinion.

As you can imagine, the implications of just these two technologies can be massive. The degree to which they already have been significantly influential is, however, unknown and therefore arguable.

The quantity and one-sidedness of news stories (either real or fake) that are presented to potential voters have already increased through the use of social media. Improving the possibilities to further personalize this communication through either real or fake news makes form a serious potential threat to a ‘clean’ democracy. A threat due to preventing potential voters to hear any other news other than what most appeals to them. This inherently prevents them from being able to up their own mind who to vote for and shifts this process to that of the analyst: who should a specific individual vote for?
Some part of the public is becoming increasingly familiar with the (business) applications of AI, partly due to its commercialization by Apple and the likes of Elon Musk. For the majority, however, AI is still nothing more than an interesting topic for a science fiction movie. And as we all know the general rule of a democracy is that the majority wins.

To mitigate these risks and in order for the public to become aware of their bias I pleed that it is necessary for a public that is better educated about these topics and their implications on our daily lives society.

 

Should you be interested in the way your personality traits (OCEAN-method) can be derived from your Facebook account, please participate in the original Cambridge-research at https://applymagicsauce.com/

 

Sources:

http://www.independent.co.uk/news/long_reads/artificial-intelligence-democracy-elections-trump-brexit-clinton-a7883911.html

https://www.economist.com/news/science-and-technology/21724370-generating-convincing-audio-and-video-fake-events-fake-news-you-aint-seen?zid=291&ah=906e69ad01d2ee51960100b7fa502595

https://motherboard.vice.com/en_us/article/mg9vvn/how-our-likes-helped-trump-win

The CEO of Cambridge Analytics about the use of big data and psychographics: