We compare the part-worth model against alternative specifications with linear and nonlinear functions for continuous attributes. We use four criteria: expected error variance of the model, expected mean squared error for average preference predictions, expected mean squared error for individual preference predictions, and a measure of the quality of parameter estimates. Although the part-worth model is generally superior to the alternatives, the expected validity of conjoint results can be improved with idiosyncratic functional forms. Continuous functions also offer an opportunity to the analyst to impose constraints on the parameter estimates.
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