Hands-on option

Basic stage for the hands-on option

Interacting with the in-class simulation, seek answers to the following questions:

• Which, if any, of the statistics are affected, and how, by the way in which the worker is assigned to each client on their first visit?
• Which, if any, of the statistics are affected, and how, by whether or not the client will always want the same worker on subsequent visits?
• What would be a good rule of thumb, if any, for the lounge capacity as a function of the number of workers? How did you arrive at that hypothesis?

In-depth stage for the hands-on option

Continue the exploration to address one more aspect of the operations. Barbershop has control over the lounge capacity, but not over the client patience (the churn threshold). Fix all other aspects of the simulation except those two and explore how one might be able to define the smallest lounge capacity at which churn (the proportion of clients lost to either excessive waiting or a full lounge) become neglible.

Conceptual option

Basic stage for the conceptual option

Watch an introductory video of what queuing theory is (this curated example or another one of your choice) and then read a scientific article (please pick one that has a DOI) in which it is applied to a topic of your interest (for example DOI 10.5812/atr.7177 but you can use Google Scholar or similar and search for "queuing theory" with additional search terms to define what interests you).

Make a list of any unfamiliar concepts. Consult each concept on the list in the glossary and fill in the feedback form to suggest the inclusion of any that are absent.

Summarize, in your own words (without resorting to an AI tool to summarize the text, that would not be acceptable for an assessment unless explicitly requested in the instructions), the utility that you perceive queuing theory to have in the application area discussed in the article.

In-depth stage for the conceptual option

Skim over the article DOI 10.1007/s10115-016-0995-z and summarize in your own words (again without resorting to an AI tool to summarize the text) how data analysis can be used to reduce churn.