About the crashcourses  

There are 10 online crashcourses. These crashcourses are linked to the Technology Impact Cycle Tool ( This free online tool, powered by Fontys University, helps you design, invent, deploy or use technology that makes a (positive) impact on society. The tool offers quick scans, improvement scans and full questionnaires. The tool consists of 10 different categories.

You get the most out of the tool when you are informed on the different categories and, even better, inspired about the categories. That is the goal of this crashcourse: inform you and inspire you on STAKEHOLDERS AND PLATFORMS, so you are better equipped to assess the impact of technology.  All crashcourses take an hour to compleet.

About this crashcourse
This online crashcourse is number five: stakeholders and platforms. In the Technology Impact Cycle Tool is a category considering stakeholders. However, we also like to introduce platforms (and blockchain) in our crashcourses. That is why we use platforms and blockchain to inform you on stakeholder – analysis! This course, like every course, has one mandatory assignment to help you understand the topic. During the course we will offer all kind of further optional suggested reading, watching and optional assignments for those who crave for more!

The goal of this course is to educate you! To inform you! To inspire you! To entertain you! To dazzle you! To make you think! That is why we did not design a boring crashcourse for beginners, or a basic course with just theory. We cherry picked our way through the topics with the aim to interest, inform and inspire you! If you think we failed you, no problem, we are open for improvements. Just sent us an e-mail on:

Some time management directions 
Again: it will take you approximately one hour to complete this course. This course consists of text, articles, videos and assignments. Every section lists reading time, viewing time and assignment time, so you can plan accordingly. If it takes longer than one hour, maybe that means your slow, maybe it means we calculated poorly. You figure it out yourself.


This 60 minute online crashcourse consists of the following sections:

  1. Platforms: a definition (10 minutes)
  2. Platforms: impact on society (Uber & AirBnB) (6 minutes)
  3. Governance & The next wave: blockchain and decentralized autonomous organizations (30 minutes)
  4. Stakeholder analysis (9 minutes)
  5. Applying the analysis on a platform (5 minutes).


Reading time: 8-10 minutes / viewing time: 1 minute

You hear a lot of people talking about the platform economy. They talk about, Facebook, Uber, AirBnB, IAAS, PAAS, Amazon, sharing-economy, gig-economy and so on. Most of the time it is pretty vague. Just watch this one minute video on the platform economy that will tell you exactly nothing.

So, we have to be more precise. Let’s start with the boring but crucial part: a definition. We must first know what we are talking about before we can form an opinion about it and look to the future.

When you read books about platforms or the platform economy, the first thing you notice is that there are quite a few attempts at definitions. The second thing to note is that these definitions are often opaque or confusing. For example, the platform economy is often used in the same breath, or as a synonym for the sharing economy. Later in this crashcourse we will see that these are really completely different things.

A definition of the platform society that is common is the following:

“A technological, economic and socio-cultural infrastructure for facilitating and organizing online social and economic traffic between users and providers, with (user) data as fuel.”

I have read this definition a few times and I must say, it is pretty good. At the same time: I don’t feel it. I do not immediately have a clear image of what platforms are. I am not immediately interested. I do not immediately have a feeling about the framework, the scope, the impact or the different platforms. So, let’s start with this definition and try to breathe some life into it.

To do this, we use the picture above. Let’s start with the middle-part: architecture (also called: infrastructure).

The infrastructure (or architecture) of platforms is shown in the bottom center of the picture above. This part is divided into several blocks. At the very bottom you have the infrastructure platforms. You can consider this the same way you consider an electricity network or a road network. They are preconditions for so called ‘higher platforms’. Without the web there would be no Facebook. These infrastructure platforms are currently the internet and the web, but that too will change someday. You sometimes hear people talking about the internet as if it will always exist, but that’s highly unlikely. Blockchain, for example, is an interesting candidate for a new infrastructure platform.

New platforms have been built on top of the basic (or bottom) infrastructure platforms, which are also kind of infrastructure platforms. This concerns operating systems, such as iOs (iPhone/iPad) or Android and so-called cloud services, such as IAAS-PAAS-AI. Companies like Amazon, Microsoft, Oracle and Google offer users services such as server capacity (IAAS), database capacity (PAAS) and nowadays also all kinds of artificial intelligence applications (for example text or image recognition). In this way, higher platforms can build new services very quickly. For example, if you have a great idea for a new app, you can programm it on iOs, make it available in the App-store, distribute it through the internet and get scalable computer capacity from Amazon.

This also means that there are certain players who are much more powerful than others!

Above the infrastructure platforms, we see the platforms we often talk about. Platforms that people use. For example Facebook, Uber, Taskrabbit, AirBnB and Dutch weather-app: ‘buienradar’. Some platforms are kind of an ‘end point’. Other platforms actually form a platform themselves. For example, Facebook offers the possibility to build other platforms on Facebook. Uber, on the other hand, does not offer that option. You can’t build a pizza delivery service on Uber yourself. Uber does that themselves (Uber Eats). It is also important to know that the platforms together form an ecosystem with large and small players. For example, you log in to Zoom (a video conferencing platform) with your Facebook-account. Also, mostly, a lot of data is exchanged between platforms. And there is a lot of sharing. For example, you can share your Spotify-activity on Facebook. Below you can see an overview of the platforms of Fernando van der Vlist (from 2016, so already a bit dated now) that makes it clear that there are large and small players and that there really is a large ecosystem.

Okay, so we looked at the architecture (or infrastructure). Now, let’s take a look at the characteristiscs of the platforms. Looking at these charasteristics helps us to understand how these platforms work. Here we go:

  • Ecosystem. We have already said it, but we would like to repeat it again: the platforms work together in an eco-system. This is the only way they can be understood;
  • Data. It’s all about data. The revenue model most of the time has to be understood in terms of data. Platforms share data, but they also make data available to each other. Sometimes they also make data available to the community. By looking at the data and data rules (what is collected, shared and with whom) you start to understand the platforms better;
  • Coded world view. The platforms are often market leaders. They match supply and demand, but they do not do it neutrally. They do this based on a certain world view, which they have translated into code. Understanding those principles is crucial to understanding the platform. However, the platforms are often unclear about their code, especially because this information is important for their competitive position or because there is a difference between their ‘message’ and their operation;
    A simple example: if you order an Uber, does the driver see your ethnicity? Does the driver know your planned route? These simple decisions are very important in terms of fairness and discrimination and far from neutral.
  • Network effect. Platforms need a network effect to be successful. The network effect works as follows: if a platform gets more users, services will be better, that will draw even more users, which will lead to even better services. This way a platform grows exponentially. The result however is that only a few winners remain. The network effect also works the other way around, so you can lose your marketshare really fast, especially if your company consists of only software (which is easy to ‘copy’). Understanding this effect also helps you understand the operation of the platform (growth, growth, growth and fear of competition);
  • Transaction costs are reduced. An important feature of platforms is that they are able to reduce transaction costs. That is their unique point of sale. These costs apply both money (for example Uber / AirBnB) and effort. Selling second-hand stuff used to be very complicated, you had to go to a market or wait for Queens/Kings Day or place an advertisement. Now it’s click, tap, swipe, tick! Another example, insulting someone used to be difficult. First you had to write a letter and sent it to the newspaper or go somewhere physically with your message. Now it’s click, tweet, swipe. Another person offended! To understand platform you have to look at the reduced transaction costs;
  • Global. Platforms operate worldwide. This has consequences for regulations (which are often national) and paying taxes (which they often do not);
  • Prosumers. Not only do platforms match users and providers, they also make these roles very fluid. Consumers are producers and vice versa at the same time (for example YouTube). The strict thinking in the separation of these roles no longer works.

Okay, so, we looked at the infrastructure and at the characteristics and now we understand platforms a bit better. Next up, is looking at the different categories of platforms. We do this by looking at the different purposes of the platforms. Here we go:

  • Do – democracy (participatory society). These are platforms that facilitate public participation. Think of health care, charity, having a say in governance, maintenance of public space, keeping the neighborhood safe together, and so. These platforms can be designed for this purpose like GoFundMe (charity), Pager (healthcare), NextDoor (neighborhood) or used for this purpose: Twitter (governance participation) or WhatsApp (neighborhood safety);
  • Product – Service economy. These are platforms that can more easily offer products and services. AirBnB (houses), Uber (rides), Facebook (News), Twitter (News) and Amazon (everything);
  • Sharing – economy. Platforms that share spare capacity. Such as Peerby (renting tools from your neighbor), Couchsurfing (places to stay), Blablacar (rides), AirBnB (places to stay), Taskrabbit (spare time – shores) and so on. A lot of platforms pose as examples of the sharing economy, but they are not. They are just product-service platforms. Uber is not about sharing your car, it is about delivering a product (a ride). Most AirBnB-activities are not about people sharing their house when they are on a holiday, but it is about renting out a empty real estate.
  • Second – hand economy. Ebay (Stuff), Marketplace (Dutch, stuff), Vinted (clothes);
  • Gig-economy. Uber (rides), Taskrabbit (shores), all kinds of coding platforms, MOOCs (education), etc …
You can immediately see from the different examples that it is not easy to divide the platforms into categories. Some are active in several categories. In addition, it is not always easy to distinguish the public relations of the platform from the actual activities. AirBnB, for example, likes to pose as  a representative of the sharing economy, but is designed in such a way that it is also very useful (and especially acts) in a product-service economy.
Finally, let’s look at the three mechanisms that all platforms use:
  • Commodification. Transforming objects, actions and ideas into tradable goods and products. That sounds like a complex sentence, but think of examples such as:  conversations become data (WhatsApp). Free time becomes a paid job (Taskrabbit). Knowledge becomes a value proposition (LinkedIn). Empty real estate become rentable space (WeWork).
  • Datafication. Every action on the platform is converted into data. This is used to optimize the platform, but is often also part of the revenue model. The exact datafication is unclear. There is a shadow layer (optional suggestion: this essay on surveillance capitalism which is part of crashcourse two).
  • Selection. The platform also does all kinds of selection mechanisms. It is unclear exactly how that works. This selection often takes place on the basis of reputation (ranking) and by the public. Where previously the selection was made by art connoisseurs, journalists, culinary critics, film connoisseurs, the audience now plays a large role. However, how that works is very unclear (for example, GoFundMe selects charities, but on what grounds!). There is a lot of criticism of selection. Whose goals are served? Who is selected? Why? Does this lead to mediocrity?

These three mechanisms are very important to understand. It also means that non-profit platforms can still generate very commercial behavior among users or fierce competition in society. Let’s say you have a platform that works like AirBnB, but it pays taxes and is non-profit, than still there is competition between house owners.

Further suggestions:

Key Take aways:

  • To talk about platforms, you have to understand what they are;
  • Important is to understand the infrastructure, the characteristics, the categories and the mechanisms;
  • Most important is to know that platforms work in an eco-system and that they are never neutral;
  • The impact on society is best understood if you look at the mechanism, especially selection and commodification.


Reading time: 6 minutes

Okay now we know what platforms are. To understand the social impact, we look at two examples, which we elaborate below: Uber and AirBnB. Admittedly, they are not the most likable platforms, but they are very large, so they make great examples.

(1) Uber
Uber was founded in 2009 by Trevor Kalasnick. The history, spectacular growth and various parts of Uber can all be found online. We are concentrating here on the Uber service in the Netherlands. This service is sometimes labeled as something from the sharing economy, but it is not. Uber in the Netherlands is a product-service platform. In the Netherlands Uber drivers comply with the rules and have the correct permits. Uber ensures that supply and demand are matched. This has a number of advantages and disadvantages and a number of consequences that are neutral.


  • Every time Uber appears in certain areas or cities, the number of complaints about existing taxi services decreases. Existing power blocks are unraveled;
  • Uber offers an opportunity to earn money or to work as a freelancer;
  • Uber leads to competitors with different, sometimes better business models, for example Lyft;
  • Uber is a prelude to thinking about new modes of transport. For example, you can link Uber with all its data to public transport. A different approach to traffic jams and the use of public transport is possible;
  • Uber and similar services are great for users;


  • Uber and similar services have a lot of data. This has high public value. However, it is not clear if and how this data can and will be shared with public authorities. Therefore, some steps cannot be taken, such as better public transport or transport in a city;
  • The concept of trust changes completely. While confidence is decreasing in institutions (police, banks, municipalities) it is increasing in each other. After all, would you sooner board a stranger? Uber ensures, through reputation systems (which can be criticized), that other forms of trust arise.
  • There is pressure to adjust regulation. Thanks to new players, new rules suddenly have to be considered. This reflection often goes ad hoc because it lacks empirical insight. It is often difficult to understand how and how often platforms are used. Platforms are hiding behind – oh, irony, privacy rules – and of course this information is sensitive when it comes to competition;
  • Prices are not determined by the driver, but by an algorithm. There is no autonomy for the driver (there is no cheaper price for an old woman). On the other hand: an old lady using Uber may also be far-fetched;
  • You can only properly regulate the platforms if you have a vision for innovation. What don’t you like and what do you like about it?


  • There is unfair competition because Uber is losing big money. This is called value creation. In Finland, for example, there was a competitor called KutsuPlus, built by the government, which had a costprice that was three times more expensive than Uber;
  • Uber does not take the responsibilities that a taxi company does when it comes to employee insurance or medical expenses. The freelancer construction is sometimes bizarre. For example, Uber called his drivers in California as non-essential. Not employees, whatsoever. However, like other platforms, Uber is losing lawsuits everywhere. They don’t get away with seeing themselves as mediators;
  • Tax is usually not paid in the country where the service takes place or the product is sold. Most of the time, tax is not payed at all;
  • Uber is ‘opaque’. The rules on the basis of which drivers are assigned, customers are picked up, prices are set can only be understood by analyzing the results. Uber does not communicate about it, and changes it all the time. In this way there can be racism (there are stories about it), because, for example, the driver can see the ethnicity of the customer and refuses. On the other hand, the driver does not see the length of the trip beforehand;
  • Uber is a company that takes all kinds of freedoms with which a Dutch company would not get away, but that is a broader problem;
  • Suppose you have to choose: be run over by a taxi – central – taxi or an Uber. What do you choose?
  • In America, Uber has caused enormous disadvantages for drivers with a taxi medallion. This pension for cab drivers has sometimes become worth 250k less because of Uber,  company that has never made a profit.

Ripple effects
It is also interesting with platforms to look at the ripple effects. At Uber you hardly see those in the above advantages and disadvantages. This is because the ripple effects are not too bad and / or are not yet clear. It is mainly about the impact on users and drivers. However, Uber claims that people in poor neighborhoods use Uber to go to work which is kind of ironic. And that Uber leads to much less traffic in and around busy cities. However, both statements are difficult to substantiate.

Further Suggestion:

  • Superpumped, the battle of Uber, book insite Uber;
  • Great article on NY Times on NY Cab drivers losing money because of Uber;
  • Six reasons why it sucks to be an Uberdriver (or why it sucks to work for an algorithm) – video 5 minutes;

A company with a lot more ripple effects is AirBnB, so next let’s look at this company. Again we look at the disadvantages, the neutral impact and the cons.

(2) AirBnB (accomodations)
AirBnB, named after the founders’ Air Mattress, was founded in 2008.  Unlike Uber, AirBnB has produced a lot of ripple effects. They are therefore more prominently reflected in the advantages and disadvantages below. The matters that also apply to Uber are not included below.

Optional assignment (1): AirBnB is not available in just a few countries in the world. Can you guess which ones?


  • It is nice and cheap for the customer, although some research has shown that often this is not true. Also, the quality of the accommodations is often better, especially for families;
  • It is good for the landlord. He can earn extra income with space that is (temporarily) vacant;
  • It has the potential to mean a lot in the sharing economy with the idea that people get to know each other better (if you rent a spare bedroom);
  • It leads to more tourism and thus to more money for a more vibrant city;
  • In a number of cases it has contributed to the improvement of less good neighborhoods due to the influx of tourists;


  • Again some remarks about trust, empirical data and the vision on innovation (see Uber);
  • The rented rooms must comply with the same laws as hotels, but who is going to check that?
  • Public interests are not automatically guaranteed. The algorithms are a-moral;


  • A lot of research has been done showing that the economic costs of AirBnB are higher than the revenues;
  • AirBnB is not inclusive. Those who have, benefit much more than those who do not have (if you have property in an expensive neigborhood, you can rent it out);
  • Living in a city is becoming more expensive. That is good if you have a house, but it is not good if you want a house;
  • Inequality continues to increase. Rich people get richer, people with less money are driven out or cannot buy a house;
  • Like Uber, AirBnB is has coded worldview which is opaque. They don’t tell you how much they rent out, they do not give data to the city. The reason they give is privacy, the reality is probably fear of the network effect (landlords go to other sites). That is why they keep the data to themselves;
  • There are further ripple effects such as atmosphere in the city, ‘Disneyfication’ of the city and increased flights, because there are more (cheap) accommodations everywhere , which in turn is bad for the environment;
  • There are stories that AirBnB is much more difficult to use by black people who are ignored. There is even a NoirBnB;
  • No tax is paid by AirBnB in the rental country, but there is no control over the landlords either;
  • The hotel industry is getting hit in some regions, and it is highly questionable whether that was an industry that needed innovation;

Further suggestions:

  • Is AirBnB ruining cities (video: 8 minutes)?
  • Impact of AirBnB on housing (article on Forbes);
  • Positive effects of AirBnB, article on medium;

Key Take Aways:

  • Platforms have a lot of influence on (parts) of society;
  • There are way more effects than only the supplier and user of the service. You can be effected even if you are not an user;
  • Government is slow to react, because most platforms do not ask for permission and are not transparent;
  • If the cons outweigh the disadvantages depends upon where you are;


Reading time: 2 minutes / viewing time: 20 minutes / assignment: 8 minutes

First watch this video (5 minutes):

The idea of a DAO is that the underlying platform may be replaced by Blockchain. Today we still deal with to companies, but soon maybe we will be talking to code. Everything is ‘connected’ thanks to the rise of the internet of things. This offers new opportunities for new platforms and new business models, compared to the current gig-economy that is still in its infancy.

Let’s look at some examples:

  • There is a project that strives to have autonomous cars in Paris. These cars can be reserved with an app and payed in cryptocurrency. If the car earns enough money, he will buy a new car. And another one. This is how the car itself starts a business. When the car is broken, the car sends a message to a mechanic, which is also paid in crypto-currencies. In the meantime, the charging stations have the same earnings and growth model. Within no time transportation in Paris is organized by code;
  • In Eindhoven, in the future, there are sensors in the grass. If the grass gets too long, a signal is sent to people with a lawn mower. They come to mow, the sensor checks and pays these people in cryptocurrency;
  • People with a screwdriver and an app replace batteries of sensors everywhere, and receive micro-payments for that;
  • Teachers no longer belong to a school, but are their own brand. Pupils are trained somewhere, and are given micro – credentials;
  • And so on.

That may mean that the call of former presidential candidate Elizabeth Warren, who wants to split up Big Tech, may be too late. Soon there will be shadowy compositions of code and micro-payments will be skimmed everywhere. All the more reason to think hard about governance. This is very, very complex, but here are some ideas that might help:

  • Regulate. Make sure that this regulation is not normative, but focuses on verifiable facts, such as: transparency, fair taxation, good use of data (GDPR);
  • Ensure that the platforms comply with Open Standards to combat the network effect. I would like to participate in a WhatsApp group with Telegram. Or I would like to have a videoconference with Zoom with someone using Teams;
  • Use existing rules, or try to interpret them for platforms. Can you refuse a platform? Is that protectionism? How does that work?
  • Establish one supervisor in one ministry. Now there are often far too many responsible / agenda holders. The supervisor organizes the political discussion. This requires a vision of society (inclusivity) and innovation.

This sounds simple, but it is very complex. Just a few questions:

  • Can you ban Spotify in the Netherlands if you think they treat artists unfairly? What would consumers think?
  • Can you block AirBnB if they refuse to transfer data?

It remains very complicated, but for now we should not expect too much from consumers or the big companies. We also have seen in recent years that the power of the big companies corrupts. So solutions should come from the authorities.

Mandatory assignment (8 minutes): In the statement above, we said that power corrupts the Big Tech companies. That is why thinking about the impact of platforms is so important. Download this PowerPoint and read the statements. Some are true, some are false. Do you know which ones?

Now, finally, with all the above information in mind, and before we go into the stakeholder analysis, watch this 15 minute video on The Good, The Bad and The Ugly of platforms.


Reading time: 7 minutes / viewing time: 2 minutes

Most stakeholder analysis – methods or literature focusses on identifying and assessing stakeholders in a project or in an organization. In this part of the crashcourse we focus on identifying and assessing stakeholders of a certain technology. There are no predefined methods for that. There is just common sense and four main questions you can ask yourself:

  1. Who are the stakeholders? (Yeah, you did not see that one coming, did you?)
  2. How are my stakeholders affected?
  3. Do I really understand my stakeholders?
  4. What stakeholders do I want to take in account?

Who are my stakeholders?
This is probably the most important question because if you miss a stakeholder this can cause a lot of problems later on. Their are a lot of stakeholders that are quite obvious for a certain technology. Let’s make a list of people that are directly affected for a simple technology: the digital camera.

  • People who buy a digital camera;
  • Companies that buy digital cameras;
  • Companies and stores that sell digital cameras;
  • Companies that have to do the services and repairs on the digital cameras;

Then you get a lot of stakeholders that are indirectly affected (and remember this list is far from complete):

  • Companies that sell analog cameras;
  • People that want to buy digital cameras but do not have the means;
  • Companies that are going to sell digital photo – albums;
  • And so on…

And then you have a list of stakeholders that are indirectly-indirectly affected (and this list really, really is far from complete):

  • People that do not want to be photographed;
  • Portrait right and privacy advocates;
  • Photographers that were old-school-superstars being pushed out of the market;
  • And so on…

And there are lots and lots more. Way to much to take them all into consideration. That is why it is important to also think about the next question.

How are my stakeholders affected?
In this phase you try to find out how your stakeholders are affected. You write this down in a few words. It doesn’t have to be a complete analysis. You will find, that if you are doing this, then you sometimes will think of new stakeholders.

The first two questions can best be answered in a multidisciplinary group. Conducting some kind of brainstorm-session is highly recommended.

Watch this video on brainstorming (2 minutes):

And still you will find out, that when your technology goes live, you will find out you missed some stakeholders.

Do I really understand my stakeholders?
A common misconception in the steps above is that you think for your stakeholders. You think people will like or will not like something, but do you really know? Let’s look at an example.

Suppose, you are a company that sells Robot Vacuum Cleaners. One of the stakeholders you have identified are house maids. You think they will not pleased with your technology because automatic vacuuming means that people have less need for domestic help and that this will negatively influence the earnings of the house maids. But after you talked to some maids, you learned that most of them do not have enough time to finish all the shores. This leads to unhappy customers and a lot of stress. A robot vacuum cleaner will free up time to do the other shores better and will lead to less stress and more satisfaction.

After you have identified your most important stakeholders, best is to consult them and not assume what they think. Consulting your main stakeholders will really help you to determine the impact of your technology.

Take into account?
Finally you have to think which stakeholders you want to take into account when designing, using or selling your technology. Let’s look at this example of a Griefbot.

First read this article on Huffington Post (3 minutes).

Further suggestions:

  • watch this video on a social bot (5 minutes):

So, a griefbot is a chatbot (or in the example above a talking head) that is based on the data trail of the deceased. This way you can still have a chat conversation with someone that has died. The griefbot uses all data-objects that have been created by the deceased. For example WhatsApp-conversation, LinkedIn-pages or Facebook-posts. By using advanced AI the griefbot learns the tone of voice of the deceased.

You can probably think of a lot of stakeholders with products like this. Suppose you also identify fundamental Christians are a stakeholder. They will not like the idea of a Grief Bot. You can take this seriously. You can communicatie with them, , inform them, maybe even change your technology.

But you can also choose not to take them in account. Choosing which stakeholders to take into account and which stakeholder to ignore, is also an important choice.

Key Take Aways:

  • Indentifying stakeholder is very important, use a brainstorm to do so;
  • Make sure that you interview or consult the most important stakeholders;
  • Choose which stakeholders you want to take into account if you are designing, using or assessing a technology.


Reading time 3 minutes / viewing time 2 minutes

In this example we have a imaginary platform called HelpingHandz. HelpingHandz is a kind of TaskRabbit. To get an impression, watch this video (2 minutes):

This platform is pretty straightforward. People that have spare time and skills can advertise them on the platform and on the other hand, people that lack spare time and/or skills can look for help. So, meet Tim. Tim is really good at hanging paintings, can drill holes in any wall and has some spare time. So he made an account on HelpingHandz and advertises his skills. Meet Angela. Angela has this beautifull painting and this empty wall and no skills whatsoever. So, Angela finds Tim on HelpingHandz, a price is set, a painting is hanged and HelpingHandz makes sure money is transferred and both Tim and Angela review each other.

If you think about stakeholders, it is important to think about the most important mechanisms of commodification, selection and datafication.

Obviously there are some stakeholders that are directly affected:

  • People with skills and spare time;
  • People with lack of skills and/or spare time;
  • The supplier of the service / platform;
  • The connected suppliers like the webhosting company or the company that transfers the money;

Then there are some stakeholders that are indirectly affected:

  • People that have a company in small shores, and see some competition;
  • Tax institutions that worry about people doing shores for money but not paying taxes;
  • Governments that manage unfair competition;

And if you do some further brainstorming, you may think about:

  • Sport associations that have problems finding volunteers because people are monetizing their skills and spare time;
  • Neighbors that help each other less now that neighbors can sell their skills to anyone (more or less the same as it becomes more difficult to use the house of a friend when the house is on AirBnB);

Optional assignment: Can you think of more stakeholders?

For every stakeholder you can think about how they are affected and if you want to take them into account or not.

If you do some more brainstorming you can even find more (and creepy) stakeholders like people who are selected to hang your painting but end up hanging you! These so called bad actors are the topic of crashcourse six!

Key Take Aways:

  • If you are thinking about stakeholders, think about casting the net… you will find interesting new stakeholders.


Congratulations. You have completed crashcourse number five, so you got a very small taste of thinking about technology and the impact of stakeholders. An appetizer, if you want. Maybe you did some further reading, so you started on the soup. Good for you. Remember: platforms are very, very impactfull. We are more and more living in a society that is shaped by platforms and to understand platforms you have to understand their architecture, their characteristics, the categories and the main mechanisms (commodification, datafication, that drive the platforms.

Because platforms are multisided and have a lot of ripple effects they are great for doing a stakeholder analysis. An analysis for assessing, using or designing technology consists of identifying stakeholders, determining how they are affected, consulting them and deciding if you want to take them into account.

Remember: platforms are organizations that have coded their worldview.