Digital Influencer's choice of product endorsement: A perspective of congruence

To infer product fitness information, consumers often consult digital influencers who exert effort to learn and evaluate product features and then propagate information to their followers. However, influencers' recommendations are not limited to products that exactly match their expertise, which may lead followers to unfollow them. This study investigates which product (high or low congruence) an influencer should endorse and how much endorsement effort should be exerted. Using a theoretical model, we obtain several interesting results. First, endorsing a low-congruence product can surprisingly benefit the influencer if the penalty per lost follower is moderate or if the influencer has sufficiently high efficiency in reducing the perception error of this product. Second, although the influencer has high expertise in the high-congruence product, she will lose more followers when endorsing it than when endorsing the low-congruence product if a particularly small or large proportion of her followers are potential consumers of the low-congruence product. Third, when the influencer endorses the low-congruence product, the number of new followers increases with the size of the influencer's follower base only when the follower base is small and a large proportion of followers are potential consumers of the low-congruence product. Interestingly, as the size of the follower base increases, the influencer always exerts more effort when endorsing the high-congruence product but will exert less effort in learning about the low-congruence product if a sufficiently small proportion of followers are potential consumers. Finally, after taking consumers' knowl-edge about product features into account, the main results still hold, and when considering the competition between influencers, we uncover the conditions under which both influencers will choose to endorse the high-congruence product.(c) 2023 China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).