All posts by quirinepaauwe

You cover me, I cover you


Eventually, every individual is obliged to join an insurance company to cover yourself for the costs of for example damage or injury. Problems of such insurances are, amongst others, the high premiums, even though you might not even need insurance that year and bureaucracy. Wouldn’t it be great if you were able to set the price, rules, premiums and claims yourself together with a group of people?

Teambrella is a platform that is designed for peer-to-peer insurance service and backed with Bitcoin. Users have exclusive control over all the aspects of insurance to make it fair and transparent and to cope with the inefficiency of current insurance services (Kastelein, 2016). Users are able to form or join teams of different sizes online to cover each other and in which each peer is both a provider and consumer. The teammates decide how risky each person is and pay according to that.

Schermafbeelding 2017-03-10 om 17.45.08

The framework includes a decision-making layer, which consists of a server for communication and voting, and a payment layer, which is based on Bitcoin technology. The voting process exists to make sure all users have mutual control over the insurance, including new members, risk evaluation, rules and processing of payments. It is also possible to appoint proxies to vote on your behalf, but you have the casting vote. When you pay more for other teammates’ claims, your vote weight grows. Bitcoin is used as a mean of providing coverage and payment of reimbursements in order to ease the burden of payments. Each premium payment is a partly reimbursement of a claim and these payments are enforced by distributed wallets that prevent spending that is not sanctioned by the other peers. After voting, the servers automatically prepare a set of transactions from these distributed wallets of the providers to the submitted claim of the user (Kastelein, 2016).

Schermafbeelding 2017-03-10 om 11.59.36.png

Efficiency Criteria
The utility for the consumers is the fact that it is easy to use and access is available anyplace and anytime. It is free to sign up and consumers have full control over getting certain claims funded. Besides that the investments are very low. Consumers are able to get insurance at low costs and keep all the invested money when no claims are submitted. Additionally, the providers are able to vote which claim to back, so they perceive all the incurred costs as fair and they only pay for trusted members. In this way, users will be willing to switch to Teambrella, because it maximizes the joint profitability.

Teambrella is feasible and takes care of several institutional arrangements. The platform is fair, because it enforces the Golden Rule of ‘treat others the way you want to be treated’ and it aligns every teammate’s interest. Besides that, the platform is transparent. You see where the money goes and every decision in the team is made by discussion and voting, so every user has control. Furthermore, the platform is affordable, because no middlemen are present (, 2017). Also, the platform takes care of several concerns about security, privacy, fraud, failure, hacks, scams and bitcoin volatility. Finally, the founders calculated several coefficients and ratio’s, which make the platform solid (Paperno et al., 2016).

Also the institutional environment is taken care of. No contracts, obligations or policies are present. Teambrella is no business of insurance, so does not need a license. Furthermore, Teambrella resolves conflicts through its own tool; the alignment of interests and standards of treatment.

Schermafbeelding 2017-03-10 om 17.45.16.png

Teambrella makes non-transparent insurance companies unnecessary and opens up a completely new field of trustworthy and demanded peer-to-peer markets.

Kastelein, R. (2016) ‘Teambrella – A Peer to Peer Insurance System Using Bitcoin. Retrieved from:, 10th of March 2017.

Paperno, A., Kravchuk, V., Porubaev, E. (2016), WhitePaper: Teambrella: A Peer-to-Peer Insurance System., 8th of March 2017.


Hey neighbour, can I rent your drone?

Drones are becoming increasingly popular, cities are filmed from above with drones, drones can send packages and drones are even used in the army (, 2017). More and more companies and individuals are interested in using drones, but what to do when you do not own a drone or in contrary, when you have a drone, but you do not use it that often? The sharing economy is already present in various aspects of society and this is exactly where the new peer-to-peer drone rental marketplace Up Sonder responds to.

Up Sonder
Just like renting a room through AirBnB, it is now possible to rent a drone. Up Sonder is a free platform and takes only a 5% provider service fee as revenue and on top of that, a small portion of the revenue is donated to help deliver access to clean drinking water to Africa (, 2017).


Everyone who owns a drone can create a free profile and list their drone at their own price to become a provider and certified FAA remote drone pilots can also list themselves by adding their service. On the other hand, companies and individuals are able to filter and rent different kinds of drones and/or services in their direct area. The platform is easy to use and providers can manage and accept bookings from within the platform. Also, they are able to access payments, scheduling, inventory management, customer messaging and sales through the online portal. The renters on the other hand can schedule and make their payments quickly. Up Sonder collaborates with UberRUSH that picks up and drops of the drones when the rent is scheduled (, 2017).


Efficiency Criteria
The utility for the consumers of the platform, the renters, is the fact that the platform is simple and fast and can be used anywhere at anytime. It is free to sign up and create a profile. Renters will switch to Up Sonder, because they do not have to buy a drone themselves, so they save money, and providers will switch to Up Sonder, because they can still make money of (unused) drones at their own price in an easy way. Besides that, the renters and providers become part of a larger community, which is fun and in which they do not have to exchange the money and drone themselves. It saves them money and time and maximizes the joint profitability.

On the other hand Up Sonder is feasible, because the platform takes care of several institutional arrangements. Firstly, to make the platform more reliable, etiquettes are present. The renters and providers can see photos of each other on their profiles and afterwards, both parties are able to write a review. At the same time, providers are protected by the platform from damage with insurance up to 2,500 dollars and renters are offered a refund policy with three different cancellation policies. Additionally, Up Sonder has a non-discrimination policy to make sure that people from all backgrounds are treated equally. The platform takes also care of the institutional environment. When providers earn more than 600 dollars in a tax year they have to fill in a tax form and payments are made by means of established methods.

Up Sonder meets several efficiency criteria and is rapidly growing. Having a drone and using its services is made available for everyone!


The Visible Hand? Demand Effects of Recommendation Networks in Electronic Markets

When you watch a movie on Netflix, when you listen to music on Spotify, when you watch clips on Youtube, when you search for connections on LinkedIn or when you are shopping online on, it appears often that you come across a sentence like: “you might also like”, “people you may know”, “customers who bought this item, also bought…”. Sometimes this suggestion might interest you and you click on it, but that is not always the case. Why do these recommendations appear and how do companies find the correct ones to recommend? What do these products have in common and how do they influence each other?


This paper of Oestreicher-Singer and Sundararajan (2012) explains these questions by focusing on online product or copurchase networks. In these networks, related products that each have their own network position, are linked to each other. The associations among products, and thus the product’s virtual shelf positions, are visible to the customers through recommendation hyperlinks. The main result states that this visibility of networks can cause a threefold average increase in the influence that complementary products, and thus not only recommended products, have on each other’s demand levels and that it amplifies the shared purchasing of complementary products.

To come to this result, data about the copurchase network of 250,000 books sold on is collected, which is used to test how demand levels are related. The data are tested on three types of possible correlations in demand. Firstly the visible network neighbours with explicit visible hyperlinks. Secondly the complementary products without visible hyperlinks, but with related demand which is controlled for unobserved sources of complementarity that might exist regardless of a visible hyperlink by constructing three alternative sets of complementary products and finally the similar environmental conditions with similar individual or environmental characteristics of the products. Besides these types of correlations, the study found that demand is also affected by the product’s individual characteristics of price, secondary market offers, vintage, in-degree and assortative mixing.

Strength of this study is that a real life setting is used to test the interdependencies, which increases the validity. Downside however is that the study is only about books. For the generalizability, it would be better to also look at other products and services such as movies, cameras or clothing.

The most remarkable outcome, besides the main result, is probably that this visibility has a stronger influence on newer and more popular products, because they ‘use’ the attention of their network position more efficiently. Recently published products are more influenced by neighbouring products, because the effect of observational learning on sales will be smaller when a consumer already has a strong prior idea of a product. Additionally, the conversion rate of recommendations that originate from more popular products is higher and sequentially the same level of total incoming traffic from fewer, more popular sources is associated with higher demand.

This study is important, because as the importance of electronic commerce continues to grow, the ability to control cross-product effects in electronic markets has become a key strategic marketing lever for firms, especially with new and popular products, and that is exactly why you see recommendation sentences when you shop online.



Oestreicher-Singer, G., Sundararajan, A. (2012) The Visible Hand? Demand Effects of Recommendation Networks in Electronic Markets. Management Science 58(11):1963-1981.

Tsekouras, D. (2017) ‘Session 2: Personalization & Product Recommendations, Rotterdam: Rotterdam School of Management (9th of February 2017).