Abstract
Recommender system (RS) algorithms are increasingly involved in online decision making, helping consumers quickly screen large assortments by presenting the most appealing products first. However, while purporting to facilitate choice, RS algorithms might be inadvertently hindering it due to the highly attractive choice sets they produce which might contribute to choice overload. In a field experiment conducted with 23,165 consumers in two online retailers, I find no indication that a considerably altered RS algorithm that presented consumers with only the most appealing product results followed by results of diminished attractiveness hurt choice process or outcome. The findings, coupled with a follow-up equivalence analysis, suggest that a small set of highly attractive products followed by many less appealing options may work as effectively as a large set of only attractive options in terms of choice process measures. This research proposes that studying consumer psychology phenomena in the unique setting provided by RS algorithms can lead to advances in both scientific theory and algorithm design. (PsycInfo Database Record (c) 2024 APA, all rights reserved) (Source: journal abstract)