Apollo R Transport Choice Modeling

I’m designing a discrete choice experiment that explores consumer preferences in the transportation sector, focusing exclusively on private-vehicle options. I have drafted the attributes and levels; now I need a robust Apollo-R workflow that takes the experiment from experimental design through to model estimation and concise reporting. What I expect from you: • Clean, well-commented R scripts that build the choice sets, simulate or load the survey data, and estimate the models (MNL first, then Mixed Logit/Latent Class if appropriate) using the Apollo package. • Clear documentation of each step so I can rerun the code with new data later. • A short technical memo (PDF or Word) that summarises the results, interprets key parameters, and flags any policy or marketing insights about private-vehicle choice. • All outputs should run on R 4.x with only CRAN dependencies plus Apollo. Acceptance will be based on: 1. Code runs end-to-end without errors on my machine. 2. Fit statistics and willingness-to-pay measures are reported and reasonable. 3. Memo explains findings in plain language for a non-technical audience. If you have prior examples of Apollo implementations or published transport DCE work, feel free to point me to them—seeing similar projects will speed up our collaboration. Budget: AUD 15–25