‘Bi-matching’: A new preference assessment method to reduce compatibility effects

Preference models and utility functions are often assessed by eliciting value trade-offs among attributes. Prior research has shown that trade-off judgments can be biased in systematic ways: for example, the attribute which is used as response receives more relative subjective weight, i.e. the so-called scale compatibility effects. This paper proposes a new procedure to elicit value trade-offs called bidimensional matching, or ‘bi-matching’, designed to alleviate this effect. Bi-matching differs from traditional trade-off judgments in that both attributes are adjusted simultaneously to reach indifference judgments. Bi-matching is compared with simple matching and choice in four experimental studies, to measure preferences for lotteries and riskless multiattribute alternatives. The main results are: (1) bi-matching produces trade-offs intermediate between those derived from matching on the ‘more important’ attribute and matching on the less important attribute, although closer to the former; (2) the trade-offs derived from choice reflect more relative weight on the more important dimension than those from bi-matching; (3) bi-matching appears to reduce response error compared to standard matching. These results are generally consistent with theoretical predictions. We discuss the normative question of which preference assessment method is preferable. The current results as a whole and the built-in features of the bi-matching procedure already position this elicitation method as a worthwhile alternative to traditional methods for helping decision-makers introspect and construct their value trade-offs.