Communicating multiattribute preferences: An experiment

The field of matching has recently made significant strides in the development of mechanisms for allocations, particularly where participants may express preferences over distinct attributes. In some applications, the preferences are multidimensional and often should be reported separately. For instance, in matching cadets to military branches in the US, participants report not only preferences over the branches but also over the length of the contract. In Chinese college admissions, applicants report the university, field of study and tuition waiver as separate attributes. This raises a practical issue of the potential complexity of preference reporting by participants. While theory ignores this complexity and assumes that agents could rank all possible combinations of attributes, practitioners challenge this view and often opt for separate ranking of attributes, which typically leads to welfare loss, as the prominent mechanism needs to operate on a single ranking. The loss can be especially high if the different attributes might exhibit complementarities and the payoff is not monotonic in quantity.

Our study aims to develop and test preference reporting methods that effectively balance theoretical richness with practical simplicity for participants. To this end, we examine six preference reporting methods under three levels of preference complexities. One method is the richest—ranking the smallest items, which we call "bundles," i.e., all combinations of attributes. It reaches full efficiency in theory under any complexity of preferences but is behaviorally complex. Two other methods are simpler and currently used in practice but limited in expressing complex preferences, leading to efficiency loss theoretically. The last three, our contributions, that we hypothesize will improve efficiency by simplifying the task of reporting.