Discriminating between decision strategies in preferential choice
When making decisions about products or services, consumers weigh up the competing options by assessing the individual attributes of each alternative. The decision strategies in the literature vary in their complexity and the assumptions about attribute processing. One assumption includes processing attributes in serial or parallel or integrating attribute values early in the decision into a utility for each option. Another assumption of these decision strategies is whether the decision can be made on partial information or only by exhaustively processing all attributes. I have classified the decision strategies by these assumptions and used the methods of Systems Factorial Technology to discriminate between the various strategy sets. Previous work has applied this in veridical choice experiments, but the current work extends this into a preferential choice scenario.