Current use of matching markets and opportunities of aplication


In this chapter, we saw different tools and algorithms that are useful to solve different allocation problems; as the ones we saw in class (marriage market, house allocations).

Matching markets, has been a topic that has risen in recent years specifically after in 2012 Alvin E. Roth and Lloyd Shapley won the 2012 Nobel prize for the “Theory of stable allocations and the practice of market design”

What draws my attention, in the how this models can be used in everyday activities and problems. The perfect example is the kidney transfer problem:

Currently, they are around 100,000 people in the transplant list in the states. The waiting for a transplant can go even from 5 to 10 years.

Patients are prioritized by how long they’ve been waiting, their blood type, immune system and more factors. By having this set of rules and characteristics in the matching of the kidneys, this market can be seen as a complicated one.

The kidney transplant matching market that we saw, is interesting because it provides a solution and a more efficient way to help the market work in a faster way, where human lives can be saved.

An interesting point is to analyze how this models and tools can be used in different areas. Nowadays the technological development might bring opportunities to use this models in the problem solving or business development areas.

For example,

Thinking about it, many new popular apps are using matching model tools in their business.

Tinder- being a matching market between people (dating app).

Uber- being a matching market between travelers and drivers.

Airbnb- being a matching market between travelers and hosts

This tools can help us nowadays in everyday activities and problems.



Hi Regina!

I also find interesting how the companies are taking advantage of the technological development to improve the markets; almost any could be improved nowadays.

I have already seen this applied to the labor market in a very unique way on They are matching potential candidates with companies that are looking to hire, based on their zip code, across more than a 100 job websites. The algorithm only notifies the candidates that fit the profile of the job offer and invites them to apply within hours! They are proud to say that “80% of employers who post a job on ZipRecruiter get a quality candidate through the site within the first day”. (Talk me about 21st century efficiency!)

Essentially what the apps are trying to do is, creating an algorithm that reduces the possible budget sets given some specific criteria such as looks (in the case of any dating app), distance from your location, waiting time, specific dates and even price!

The kidney market is a very popular example but, as some other peers have mentioned in other posts, it’s quite controversial. Another application of these algorithms, to health related markets, could be applied to medical consultations. Imagine an app that matches physicians with patients where you could filter by specialty, seniority, hospital, if they do home consultations or any other characteristic that you could think of.

José Pablo Herrera De La Llave