An agent-based model to analyze consumer purchase behavior
I developed an agent-based modeling that represents a synthetic population in a neighborhood. A micro network is created for each household based on the locations people typically travel every day (work, day care center, grocery stores, etc.). People interact with the infrastructure in the neighborhood. Presence of electric chargers at home, work or public as well as hydrogen stations influence their purchase behavior.
The model predicts the purchase probability based on a multinomial logit approach in real-time based on the daily driving pattern of the neighborhood. The model runs for a year.
Click here for more details. The model file is also available to download from the Github link.