In the following project I am a creative designer at Nike. Nike is an American retail store that offers a wide range of products such as footwear, apparel, equipment, accessories, and services. With the growing concern in global warming I would like to conduct research to see if there is a market for Nike to produce a new streetwear shoe made from 100% recycled materials. In a recent study at MIT, a typical pair of running shoes was found to generate 30 pounds of carbon dioxide emissions, that is equivalent to keeping a 100-watt light bulb on for one week. While the majority of emissions are generated during the manufacturing process of the shoe lifecycle, by using recycled materials we are able to manufacture less new materials thus causing a decrease in carbon dioxide emissions.
The target population I am interested in is going to be the entire US adult population. While it is a bit broad, I picked this population because I would like to get an idea of what the ideal customer would look like for this type of product. Since this will be Nike’s attempt to enter a new niche market, we do not want to start the analysis with a segment in mind and leave out potential buyers.
I have included the SAS (.egp) file which goes over the variable selection and data cleaning process, as well as dimensionality reduction and clustering techniques. This code can also be found in a word doc just in case the file extention is an issue. I also included an R (.Rmd) file which reviews a few additional assumption tests for the dimentionality reduction and clustering techniques. Lastly, I have added a write up that should help explain the entire project from a high level.
If you should have any questions about the code or analysis please feel free to reach out!
-Amber Arriaga