Manipulating Users’ Trust of Autonomous Products With Affective Priming

Abstract

Autonomous products, which perform many functions on their own with limited user input, require users to exhibit trust at an appropriate level before use. Research in product trust has thus far focused on the product characteristics: such as manipulating the product’s design—for example, anthropomorphizing an autonomous vehicle—and measuring changes in the users’ trust. This study flips the usual approach and instead manipulates users’ mental state through priming, and then measures users’ trust to an existing autonomous product, the Amazon Echo. In this study, we used visual stimuli (images) that evoked either positive or negative emotions as affective primes to influence users’ trust before interacting with the Echo. While interacting with the Echo, users evaluated its performance and how well it met their expectations. Holistically, users’ perceived performance of the Echo and age had significant effects on their trust of the product, but the affective primes showed no significant effect. However, for the subgroup of participants whose expectations of the product's performance were met: those who received either positive or negative prime were more likely to trust the product than those who saw neutral images; men were more likely to trust the product than others. The study demonstrates the importance of meeting users’ expectations and highlights the potential to build trust by inducing emotions contextually.