The Effect of Choice Overload on Decision Rule Adoption

Utility maximizing and regret minimizing models (RUM and RRM respectively) assume different decision rules, and additionally that these rules are conceptually and mathematically distinguishable. Yet, studies that pit them against each other or incorporate them into a heterogeneous decision rule model find statistically similar performance. This study shows that an increase in choice complexity, measured by the number of alternatives available, can lead to switching between utility-maximizing and regret-minimizing decision rules due to the pursuit of choices better aligned with decision-maker expectations, weighed against the cognitive burden generated by the number of available alternatives. For larger choice sets, this tradeoff leads to the adoption of decision rules better aligned with goals and cognitive resources required. Using a discrete-choice experiment in a tourism hotel-booking context (n=1055), we develop a purpose-tailored choice model to empirically document that for smaller choice sets, the adoption of utility-maximizing versus regret-minimizing decision rules is roughly equivalent (52% vs. 48%), but for larger choice sets the adoption of utility-maximizing increases to 72%. This study provides a general framework to study decision rule adoption as a function of contextual factors and insights into the adoption of decision rules based on commonly used choice set sizes, thereby guiding researchers in designing choice experiments