Abstract：A new trend in influencer marketing is livestream commerce, which combines influencers’ live video streaming with e-commerce. Little is known, though, about how firms should develop their influencer strategies to maximize product sales. Given a budget constraint, marketers may choose to employ a single, “big” influencer with a large number of followers or several small influencers. They may also employ a combination of both big and small influencers when their budget is adequate. Analyzing data from 1.3 million livestreams on TikTok, the authors find a negative interaction effect between big and small influencers when employed together due to decreased trust in big influencers and substitution effects. Further analysis reveals that livestream sales generated by a big influencer are adversely affected by small influencers who promoted the same product previously, but not the other way around. In addition, big influencers can reach a much larger audience, whereas small influencers are more effective at increasing the audience’s conversion rates. Big and small influencers are also different in terms of how product and campaign characteristics moderate their sales effectiveness. Finally, the scenario analysis explores how the profitability of influencer strategies hinges on the influencer mix and their costs. This research is one of the first to investigate the sales effectiveness of influencer marketing and to provide general guidelines for developing influencer mix strategies.

主要发现：大网红负责触达，小网红更擅长转化；混用不一定叠加增效，还可能因信任与替代效应相互抵消。

Abstract：Direct-to-consumer firms increasingly believe that influencer marketing is an effective option for seeding. However, the current managerially relevant question for direct-to-consumer firms of whether to target low- or high-followership influencers to generate immediate revenue is still unresolved. In this article, the authors’ goal is to answer this question by considering for the first time the whole influencer-marketing funnel, that is, from followers on user-generated content networks (e.g., on Instagram), to reached followers, to engagement, to actual revenue, while accounting for the cost of paid endorsements. The authors find that low-followership targeting outperforms high-followership targeting by order of magnitude across three performance (return on investment) metrics. A mediation analysis reveals that engagement can explain the negative relationship between the influencer followership levels and return on investment. This is in line with the rationale based on social capital theory that with higher followership levels of an influencer, the engagement between an influencer and their followers decreases. These two findings are derived from secondary sales data of 1,881,533 purchases and results of three full-fledged field studies with hundreds of paid influencer endorsements, establishing the robustness of the findings.

主要发现：高粉丝量并不等于高ROI；当纳入触达、互动、销售与成本后，低粉网红可能更能带来收入回报。

Abstract：Influencer marketing significantly impacts consumer behavior and decision-making. However, identifying the drivers of influencer marketing effectiveness and conditions that enhance their impact remains challenging. This meta-analysis, which synthesizes 1,531 effect sizes from 251 papers, assesses influencer marketing effectiveness by examining its antecedents, mediators, and moderators. Building on the persuasion knowledge model to develop and test a framework, we identify post, follower, and influencer characteristics as key antecedents impacting both non-transactional (i.e., attitude, behavioral engagement, and purchase intention) and transactional (i.e., purchase behavior and sales) marketing outcomes. For non-transactional outcomes, follower characteristics (social identity) have the strongest effects on consumer attitudes and behavioral engagement, while post characteristics (informational value and hedonic value) exert stronger effects on purchase intention. For transactional outcomes, influencer characteristics (influencer communication) have the strongest effects on purchase behavior. These antecedents also affect marketing outcomes indirectly through persuasion knowledge and source credibility. Moderation results indicate that direct and indirect effects of antecedents depend on social media types (i.e., nature of connection and usage) and product types (i.e., information availability and status-signaling capability). These results consolidate and advance the literature and offer insights into enhancing the effectiveness of influencer marketing.

主要发现：网红营销效果取决于帖子、粉丝、网红三类因素；态度参与和真实购买的驱动机制并不相同。

Abstract：Influencer marketing initiatives require firms to select and incentivize online influencers to engage their followers on social media in an attempt to promote the firms’ offerings. However, limited research considers the costs of influencer marketing when evaluating these campaigns’ effectiveness, particularly from an engagement elasticity perspective. Moreover, it is unclear whether and how marketers could enhance influencer marketing effectiveness by strategically selecting influencers, targeting their followers, or managing content. This study draws on a communication model to examine how factors related to the sender of a message (influencer), the receiver of the message (influencer’s followers), and the message itself (influencer’s posts) determine influencer marketing effectiveness. The findings show that influencer originality, follower size, and sponsor salience enhance effectiveness, and posts that announce new product launches diminish it. Several tensions arise when firms select influencers and manage content: Influencer activity, follower-brand fit, and post positivity all exert inverted U-shaped moderating effects on influencer marketing effectiveness, suggesting that firms that adopt a balanced approach along these dimensions can achieve greater effectiveness. These novel insights offer important implications for marketers designing influencer marketing campaigns.

主要发现：网红原创性、粉丝规模和赞助商显著性有利于效果，但活跃度、契合度和正面情绪都不是越高越好。

Abstract：Many ads are engaging, but what makes them engaging may have little to do with the product. This problem can be particularly relevant to influencer advertising if influencers are motivated to promote themselves, not just the product. We develop an algorithm to measure the degree of effective engagement associated with the product and use it to predict the sales lift of influencer video advertising. We propose the concept of the product engagement score (PE score) to capture how engaging the product itself is as presented in a video. We estimate pixel-level engagement as a saliency map by training a deep three-dimensional convolutional neural network on video-level engagement data. We locate pixel-level product placement with an object detection algorithm. The PE score is computed as the pixel-level, engagement-weighted product placement in a video. We construct and validate the algorithm with influencer video ads on TikTok and product sales data on Taobao. We use variation in video posting time to identify video-specific sales lift and show that the PE score significantly and robustly predicts sales lift. We explore drivers of engagement and discuss how various stakeholders in influencer advertising can use the PE score in a scalable way to manage content, align incentives, and improve efficiency.

主要发现：能卖货的参与必须围绕产品本身，而不是只让网红或娱乐元素吸引注意；产品参与得分可预测销售提升。