Valuing Influence with Social Learning

• 成果类型: Article
• 署名作者: Ahn, Hyun-Soo; Ryan, Christopher Thomas; Uichanco, Joline; Zhang, Mengzhenyu
• 署名单位: University of Michigan System; University of Michigan; University of British Columbia; New York University; New York University Tandon School of Engineering; University of London; University College London
• 刊物名称: M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1523-4614
• DOI: 10.1287/msom.2025.0348
• 发表日期: 2026
• 关键词: information

摘要

Problem definition: Influencer marketing has become a prevalent strategy to promote products through social media. This paper examines the value of influencer marketing when followers not only learn from the influencer's signal but can also engage in social learning by observing peers' purchase behaviors and reviews. Methodology/results: We adopt an information design framework to analyze how a firm should value an influencer based on two key dimensions: the accuracy of the influencer's past recommendations (informativeness) and the extent to which followers rely exclusively on the influencer versus learning from peers (charisma). Managerial implications: Our model uncovers insights about the interaction between information design and social learning. First, the naive intuition that the influencer is less valuable with social learning does not always hold. The influencer holds greater value under the social learning context when customers have a moderate intention to buy as her endorsement reinforces customer convictions, making them resilient against later negative feedback from other followers. Second, when the firm can strategically select an influencer, the optimal information structure is biased toward the positive signals: always endorse good products (true-positive rate of one) but sometimes endorse bad products (nonzero false-positive rate). Third, the optimal influencer when social learning exists has a lower false-positive rate than the one without social learning, meaning that when there exists subsequent social learning, it becomes even more important to have an influencer whose positive endorsement is trustworthy. In other words, the optimal influencer should be able to reveal more information with social learning than without social learning.