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This study examines the role of gender stereotypes in the humanization of robo-advisors. With advances in technology, robo-advisors, or automated/algorithmic investing platforms, have become a popular option for individual investors who want the benefits of professional money management at a relatively low cost. Yet little is currently known about how individual investors interact with these tools.
The current study used an experimental design to examine the role of gender stereotypes on the humanization of robo-advisors. While a prior study by Hodge, Mendoza and Sinha (2019) showed the negative effects of humanizing robo-advisors by giving them a name, our results suggest that it depends on the gender and associated stereotypes that are used to humanize the robo-advisor. While humanizing robo-advisors with a male name had a negative effect on advice utilization (in comparison to a control group with no name), humanizing robo-advisors with a female name had a positive effect on advice utilization. These results have implications for financial services firms as they continue to venture into the realm of robo-advising.
Stacey M Whitecotton, Arizona State University - Tempe
Janet Samuels, Arizona State University - Tempe
Erin Jordan, Arizona State University - Tempe