Tags Posts tagged with "platforms"


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rating reputation platform economy

Online valuation systems are overrated. Most systems are flawed and become less and less important as trust in the brands of platforms like Airbnb and Uber grows.

At the time, in 2007, when Brian Chesky and Joe Gebbia came up with the idea of creating an online platform on which anyone could rent a room to a completely unknown tourist, they drew many odd looks. How could you know an overnight guest can be trusted? In the mean time, over 100 million nights have been booked through the platform in 191 countries. I’m talking about Airbnb. The secret: online trust through valuation systems.

Sharing rooms and houses has been existent since time began, but thanks to Airbnb the threshold has been lowered and the activity grows exponentially. There is a growing number of online platforms that link up individuals using the same principles. Uber links up drivers with people who want to travel from A to B and the Dutch SnappCar links up car owners to people who need a car for just a short time. In the Netherlands, already over 140 platforms actively mediate between individuals. Every platform’s promise: Carefree pleasure. Trust is their key.

Trust through online platforms is created in two different ways:

  1. Interpersonal Trust: The trust among users. This is created by personal profiles filled with information about yourself and through reviews of others about you. When you rent a room through Airbnb, you will evaluate the host and he evaluates you afterwards. The more transactions, the better the view on the trustworthiness of users;
  2. Institutional Trust: The trust users have in the system. Platform builders do all they can to ensure problems are avoided and solved as soon as possible. Preventive measures are, for example, profile scans and automatic processes like credit checks to keep people with wrong intentions out. Reactive measures are a valid insurance or a well-reachable customer service. These together create trust in the brand of the platform.

It has to do with both trust in the platform, as well as trust in other users. Valuation systems (e.g. reviews, stars) serve several purposes: they cause bad apples to be quickly removed from the system, they ensure that people will be chosen according to their proven quality, and they enforce certain desired behavior. At the time you misbehave (or you do not behave as per the applicable or desired standard), you’ll be slowly excommunicated and you’ll end up at the sideline.

Online evaluation in practice

How does online evaluation practically work? Most evaluations are based on a 5 star system. Besides this, most platforms offer a possibility to add a certain explanation to your evaluation in a text box.

When you look at the average number of stars in Uber, it appears that the differences between good, medium, and bad aren’t that big at all:

The impact of only one low grade can be big in case you don’t have many evaluations yet. And one low grade lowers the chance that someone else will choose you the next time. Is this current system the ideal?

Let’s take a ride in an Uber taxi as an example. That particular day, you woke up at the wrong side of the bed, the taxi ends up in heavy traffic and you miss out on an important business meeting. Chances are that you will not give this driver a great evaluation. In this example the context is independent of the evaluation.

Another example: A carpenter offers his service on Werkspot.nl. In his first year, as a beginning carpenter, he does not have the same experience as an old hand in the trade. Over the years he develops himself as an expert, though negative reviews of his first year still weigh in his reputation forever. Such a system doesn’t account for any learning curve.

Reputation and valuation 2.0

A party that, in my opinion, has thought things through really well, is the Dutch Meeting Review: a platform to evaluate event venues. They improved online evaluation in four different ways:

  1. Linear depreciation of reviews: a review is depreciated over a time of 4 years. After 1 year it’s weighed by a factor of only 75%, after 2 years 50%, 3 years 25% and the ratio becomes 0% after 4 years. This ensures that your mistake won’t be counted against you forever and your most recent performances contribute the most to your overall evaluation;
  2. Possibility to follow up on a negative review: In the Uber-example, you may imagine that a client calms down and realizes that he has given a too low valuation. At MeetingReview you are allowed to change you evaluation in hindsight.
  3. The feedback loop: As receiver you are allowed to enter into a conversation with your feedback supplier to find a reasonable solution. So, not only a future client will profit, but also the current user of the system. This feedback loop is based on the good intentions of the evaluated person and the insight that he wants to learn from his mistakes;
  4. Manual checks: With a scoring system ranging from 1 to 10, all deviating scores below 5 and higher than 8 are being checked manually. This prevents good friends or competition to affect the average score unjustly.

Such a smart valuation system is an exception at the moment. Most platforms still work with the simplest ratings. Though choices that are made, based on this output, may be drastic.

Added value of interpersonal trust in the future

First of all, more and more often algorithms make the first selection of the supply. With Uber, the algorithm makes a match between you and the taxi. Only afterwards you’re able to see the valuation of the driver. Due to the fact that this car is your fastest option, you’re not likely to decide to cancel this ride. Also on other platforms we see automated linking appear. In Airbnb you’re already able to rent many houses by ‘direct booking’, i.e. without the explicit confirmation of the landlord.

What we see happening is a movement from interpersonal to institutional trust. Ultimately, you trust the platform to have all their scans and checks up and running. And, moreover, that the platform will fix things in case it would go wrong. The role of valuation systems will be moved to the background more and more, and will end up as no more than a control mechanism.


Interpersonal trust played a big role when the institutional trust wasn’t yet developed. In 2007, nobody had heard about Airbnb, there was no trust in the brand, and besides people were asked to do something they had never done before. The interpersonal trust through online profiles played an important, though temporary, role. The ofter we use these kind of platforms, the greater the trust in the institutions behind these sites.

Be honest: What was the last time you asked your favorite airline for the online valuation of the pilot of your airplane? Exactly.

This post was originally posted on the website of Intrapreneur.nl, a knowledge platform of Trivento.


Question @RenseC on Twitter: “Doesn’t the fact that eBay reputations are still influential contradict with your theory?”


Yes and no. I think that a certain balance between interpersonal and institutional trust will always remain. The question is about the proportion of each of these, and is determined by several factors:

1. The trust and reputation the platforms has developed. Included are elements as trust in the brand, position compared to competition, how screening of users works, if quality checks are in place, what measures are taken when things go wrong, and which securities (e.g. insurances) the platform offers. For example, in case you know that Airbnb excludes every one with a score under 90% from their platform and profiles are filled well, and these elements are evaluated and checked, the necessity to look beyond to the reviews is smaller;

2. The core of the product or the service. Is the product or service standardized? Take a taxi ride through Uber: there are two certain quality standards that provide security (car type, certificate of good conduct, etc.). Besides, the desired behavior (response time, accepted score, etc.) is smartly directed through de app. Therefore it doesn’t matter if driver A or driver B provides you the ride. You want to go from A to B and that’s your reason for choosing the (brand) promises of the platform. Interesting note on the side: maybe the reputation of the demand side will be more important in the future: I’ve seen several Uber forum discussions about the question if you should pick up a client with a score of 4.3, cause it is guaranteed trouble;

3. The transaction taking place with physical contact or not; With a physical meeting (especially outside the personal living space) you’ve got more input on trust and the other party has a harder time not keeping his promises;

4. If the transaction is about a regular thing (taxi ride) or a once in a lifetime transaction (purchase of some product on eBay);

5. If an algorithm provides the match. In other words: are you able to make a choice based on the full supply, or does a algorithm provide you a match and does the profile only serve you to possibly refuse the choice made for you;

6. Choice: if there is (like traveling with BlaBlaCar from Utrecht to Brussels about noon tomorrow) not much to choose from, you’ll be less picky;

7. Urgency: do you need something fast, or may it wait for a bit;

8. What are you about to lose, when something goes wrong?

9. Probably, I’ll think of some more reasons later on 😉

Conclusion: I think the proportion of interpersonal <> institutional differs per platform and per service/product. I’m of the opinion that a strong institutional trust, trust in / familiarity with the service, small uncertainty, automated or preselected match and the urgency of the matter influence the impact and lower the requested the interpersonal trust .

To concretely answer Rense’s question regarding eBay: At eBay you may trust the institution in the way they handle their processes, but there are many uncertainties –e.g. not being able to check the quality of the product or not know the product to well yourself. With anUber ride things are organized much tidier, for their focus is on only 1 thing: a car driving from A to B while providing a good user experience. Actually, I’m curious if there is a difference in results of people that have picked up their products personally or when it had been shipped.

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Google, Facebook, Uber and Airbnb: four companies, which became dominant market players in their segment in a very short time. Uber, for example, grew in seven years to the world’s biggest logistics company. Platform-expert Martijn Arets unravels the success formula of these services.

1. Facilitation in stead of control

During the industrial revolution the trend was to centralize both people and resources. To the effect that maximum efficiency could be reached. It used to be he ideal formula, as at the time most products and services where produced by the dozen. Or like Henry Ford stated, “Any customer can have a car painted any color that he wants, so long as it is black.”

The downside of this decentralization was a lack of flexibility; changing existing processes went slow and was burdened by big inventorial investments. When we look at a platform like Airbnb, we see the opposite. Airbnb as a company itself doesn’t invest in property, though connects (private) owners of existing property (which may be rented out for leisure purposes) to people who see the need to rent it. The platform works as an intermediary with a client base, which may grow exponentially, through a (relatively) non-capital-intensive strategy. Facebook, Airbnb, Booking.com and Martkplaats.nl work all in the same way.

The great challenge of a platform is the need for two sides: the demand and the supply. The art of starting a platform is to realize a healthy balance between them. Uber does a smart job. The taxi platform governs the deployment of drivers by using dynamic tariffs. When the demand outgrows the supply, fares are raised. This motivates drivers to get their car started and demotivates the clients to task for a taxi right now. Thus, the supply increases and the the demand decreases, which immediately restores the balance.

Key learning point: Go back to the core of your company and see how you may set up your service as a platform.

2. The innovation process upside down

A second obstacle to platforms is their way to turn innovation processes upside down. Professor in Innovation Studies, Koen Frenken, calls this ‘reverse technology assessment’. He explains, “Normally speaking, an innovation is first studied scientifically, second a public discussion about its desirability takes place, then politics come up with regulations, and finally an innovation is marketed.”

This is process in place with new medicine, airplanes, food or farming methods: first research, then safety tests, next regulations, and finally market introduction. Though with the sharing economy the process is reverted. Companies launch their new platforms first, which will consequently be follow by a normative discussion, and only then scientific research.

The problem is that platforms, by doing so, knowingly violate laws and regulations. Uber knew that UberPop, a gypsy cab service, was illegal. By applying the reversed innovation process, Uber created a satisfied market first, by which it was much harder for public institutions to prohibit the service.

Key learning point: Some impertinence from time to time doesn’t hurt. And sometimes it’s better to ask for forgiveness after the event, than permission up front.

3. Use the newest technology optimally

Many activities we perform by using platforms nowadays, aren’t new. Sharing has always existed. Platforms only lower the thresholds. For example, transaction costs are lowered, and strangers may be trusted, thanks to reviews and reputation scores. The added convenience fosters a rapid increase in usage.

Let’s take uber as an example. Where it used to be troublesome to get a cab, nowadays it can be done with 3 ‘taps’ on your smartphone. The fact that both the driver and you own a smartphone, makes it possible that many operations are automated. The algorithm matches you with the closest driver. At the end of the ride you rate the driver and the driver rates you. This reputation system filters out bad performing drivers and asocial clients in no time. Linking your credit card ensures you that you don’t have to give the payment process a second thought.

Key learning point: Use technology and algorithms to simplify processes and make them self-managing.

4. Extreme focus on creating convenience

One of the key agenda points in the development of online platforms is to create convenience for both the client and the supplier. Processes are becoming simpler and more and more services are being integrated in existing apps. It is even possible to directly order an Uber from Google Maps and also KLM has integrated the Uber API connection into its website.

The next step is to look ahead to the future. The now Uber app links to your agenda and registers your daily rhythm. This in order to give you the right suggestion to order a taxi at the right time.

A Mayor point of interest in this development is of course privacy. To what extent would you be able to trust a commercial party with your personal data? That is something about which start-ups can learn a lot and where existent companies are absolutely well ahead.

Key learning point: See how you may use technology to find ways to serve your clients proactively.

5. Think in categories, not in niche markets

Uber isn’t a taxi company, but a logistics platform, and Airbnb isn’t a renting out accommodations, yet offers “unique (local) experiences”. Though many people talk about Uber as if it is a taxi company, in the mean time they’ve started to deliver food (UberEats) and are developing the platform for self-driving trucks and cars. Airbnb is aiming at the complete travel experience and not only at accommodation; hence the platform newly offers tours. This way platforms embrace the opportunity to become the all-in-one solution in their category, and that doesn’t leave much space for competition.

Key learning point: Think outside your own niche market, but think of all-in-one solutions.

This blog was published in Dutch on Intrapreneur.nl

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