Process-tracing choice quality in riskless multi-attribute decisions

Empirical findings from behavioural decision research suggest that individuals employ a range of strategies to construct their preferences when faced with multi-attribute choice problems. However, it is not well understood what information decision makers use when making a multi-attribute choice, and if training decision makers can improve multi-attribute choice quality. In this thesis, I adopted a process-tracing approach to evaluate preference construction processes in terms of quality in two behavioural experiments. Both studies involved a set of hypothetical choice problems, and utilised normative standards based on attribute range sensitivity as benchmark to compare against observed decision processes. Choice heuristics displayed efficiency and performed at least as good as strategies based on Multi-attribute Value Theory (MAVT). This result was observed consistently, independent of the prescriptive intervention stage, across experiments. MAVT-based strategies failed to unleash their theoretical potential. The study findings suggest that level of strategy execution had higher impact on choice quality than the sophistication of the selected strategy.