The purchase likelihood model estimates the stated purchase likelihood for products you specify in the simulator, where each product is considered independently. The likelihood of purchase projection is given on a 0 to 100 scale.
If you intend to use the Likelihood of Purchase option in the Market Simulator, your data must be appropriately scaled based on stated purchase likelihood. The following estimation methods result in data appropriate for the purchase likelihood option:
|1.||ACA, if calibration concepts (where respondents indicate purchase intent on a 0-100 scale) have been asked and used in utility estimation.|
|2.||CVA, if single-concept presentation was used (where respondents indicate purchase intent on a rating scale), and the logit rescaling option used with OLS regression.|
|3.||CBC/HB, if calibration concepts have been asked and the Tools + Calibrate Utilities program (from the CBC/HB standalone program) is used to rescale the utilities.|
Any other procedure will result in simulations that are not an accurate prediction of stated purchase likelihood. Keep in mind that the results from the Purchase Likelihood model are only as accurate as respondents' ability to predict their own purchase likelihoods for conjoint profiles. Experience has shown that respondents tend to exaggerate their own purchase likelihood.
You may use the Purchase Likelihood model even if you didn't scale the data using calibration concepts, but the results must only be interpreted as a relative desirability index. Meaning: a value of "80" is higher (more desirable) than a value of "60," but it doesn't mean that respondents on average would have provided an 80% self-reported likelihood of purchase for that particular product.
The purchase likelihoods that the model produces are not to be interpreted literally: They are meant to serve as a relative gauge or "barometer" of purchase intent. Under the appropriate conditions and discount adjustments based on past experience (calibration), stated intentions often translate into reasonable estimates of market acceptance for new products.
This model provides a means of simulating a product category with only a single product. The other three choice models are comparative models that require at least two products to be specified in a simulation. Likelihoods are estimated for product concepts by summing scaled utilities and estimating probabilities with the following transformation:
p = eu
1 + eu
p = probability of purchase
e = the constant e
u = product utility