Network Traffic of Internship/Project Team Applications
Source: https://mitadmissions.org/blogs/entry/my-freshman-journey-with-internships/
Game theory can be found in many processes of competitive application, as the outcome of one applicant (getting in or not getting in) depends on the behaviors of the other applicants as well. For example, the process of getting an internship in college is competitive, since there are multitudes of students applying for one position. An internship application process becomes even more competitive when the internship is especially coveted and for a well-known company such as Google. As more applicants apply for one in-demand company, the possibility of a high payoff (getting accepted) becomes more remote. An individual applicant can apply for a highly valued, competitive internship and face a high possibility of rejection (a low payoff), or apply for a lower-valued, less competitive internship and have a higher possibility of acceptance. Being accepted into the lower-valued internship would give a higher payoff than rejection from the competitive internship, but not as high as the payoff obtained from getting accepted into the competitive internship.
Competitive application processes are similar to the concept of network traffic, in which travel time is determined by the strategies of all of the cars on the road. If all cars decide to take one route because it is the fastest way, travel time will increase, worsening traffic. Similarly, a large proportion of college students may decide to apply to one highly-valued internship because it is a dominant strategy in career choice – no intern of an in-demand company will benefit from switching companies. However, the probability of acceptance will decrease because of the large volume of people applying.
In the case of project teams, there may be several subdivisions within one project team and an applicant will only be able to choose one division. If the subdivisions have similar focuses but different projects, applicants may be conflicted on which division to apply to within the project team. Their decisions can depend on the strategies of the other applicants, since there is a chance that everyone will apply to one particular subdivision instead of splitting their applications between the multiple subdivisions available. This situation is also comparable to network traffic, as many applicants will select the subdivision they think will not receive a lot of applications (the dominant strategy). They will end up lowering the probability of acceptance into the project team (the payoff) instead of increasing it through the diversification of subdivision choices.