Allocation-Based Conjoint

An Allocation-Based Conjoint (ABC) model consists in exposing respondents to a number of scenarios (tasks), where all currently available products appear next to the new product(s). Respondents are asked to assign some points to each product featured on each scenario based on the number of (multiple) purchases (the total can add up to 10, 100 or can be left free to vary across respondents to estimate overall uptake in addition to product shares).

This framework is especially appropriate for a deep understanding of the relationships between the current products and different definitions for the product(s) to be launched.

It is a popular approach to investigate prescription or recommendation preferences of healthcare professionals.

The functions ABC.logit.aggregate and ABC.logit.individual available in R-sw Conjoint allow running aggregate-level and individual-level traditional logit estimation of allocation-based conjoint data, respectively. ABC.HBlogit performs an individual-level hierarchical Bayes (HB) logit estimation. Data can easily be prepared for estimation through ABCtext2list.

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