My research examines how novel technologies and digital environments reshape firm strategy, consumer behavior, and market outcomes, using large-scale data and empirical models. My most recent work centers on two themes. The first is influencer marketing: I study how the intermediaries and management systems behind creators shape the volume, variety, and quality of the content they produce, and how platform policies and firm strategies, from monetization to content embargoes, alter what creators supply. The second is artificial intelligence in digital markets: I study how AI is changing the way content is created, evaluated, and consumed on online platforms.
Publications
Iyengar, Raghu, Young-Hoon Park, and Qi Yu (2022). The Impact of Subscription Programs on Customer Purchases. Journal of Marketing Research, 59(6), 1101–1119.
JMR Top Cited Article, 2022–2023
Abstract
Subscription programs have become increasingly popular among a wide variety of retailers and marketplace platforms. Subscription programs give members access to a set of exclusive benefits for a fixed fee up front. In this article, the authors examine the causal effect of a subscription program on customer behavior. To account for self-selection and identify the individual-level treatment effects, they combine a difference-in-differences approach with a generalized random forests procedure that matches each member of the subscription program with comparable nonmembers. The authors find that subscription leads to a large increase in customer purchases. The effect of subscription is economically significant, persistent over time, and heterogeneous across customers. Interestingly, only one-third of the effect on customer purchases is due to the economic benefits of the subscription program, and the remaining two-thirds is attributed to the noneconomic effect. Evidence supports that members experience a sunk cost fallacy due to the up-front payment that subscription programs entail. Finally, the authors illustrate how firms can calculate the profitability of a subscription program and discuss the implications for customer retention and subscription programs.
Working Papers
More than Match-makers? How Do Influencer Management Systems Affect Content Volume and Variety (with Ernst Osinga)
Conditionally Accepted, Journal of Marketing Research
Abstract
Influencer management systems (IMSs) have become essential tools for advertisers to reduce search frictions when identifying and selecting influencers, yet little is known about how these systems shape the content influencers produce. We construct a novel dataset of influencer content from top gaming channels on YouTube and examine a natural experiment created by the introduction of an IMS on a major digital game distribution platform. Our identification strategy exploits influencers’ varying levels of exposure to the IMS. We find that the IMS leads to a significant increase in content volume and a marginally significant increase in production effort. The increase in content volume is assortative: larger influencers expand their coverage of larger games, whereas smaller influencers expand their coverage of smaller games. However, these efficiency gains are accompanied by a reduction in content diversity, both within and across influencers. We further document that aggregate audience engagement, measured by the total number of comments, increases, and that influencers shift their non-IMS-managed content toward niche genres. We discuss the implications for platforms, influencers, and advertisers.
Organic Content, Embargoes, and Quality Obfuscation: Evidence from the Gaming Industry (with Zhe Lin)
Abstract
Social media influencers play a pivotal role in shaping consumer decisions in modern markets. While current disclosure regulations help consumers discern sponsored from organic content, firms increasingly employ embargoes—contractual restrictions on what influencers can share—to manage influencer content. This research investigates whether and how embargoes with varying levels of restriction impact influencers’ content, contribute to quality obfuscation, and affect product outcomes. We examine these questions in the context of the gaming industry, where influencers play a key role. We construct a unique dataset combining YouTube game review videos with downstream consumer behavior data. Based on over 79,000 videos, we develop a novel measure of “embargo stringency” that quantifies the extent of restrictions imposed on influencer content through video analytics. Our results show that stricter embargoes lead to influencer content that is less informative yet more positively skewed. Despite limiting transparency, content under stricter embargoes generates higher product interest and demand. Elasticity analysis suggests that consumers are more sensitive to negative content than to missing information. Moreover, despite the increasing use of embargoes over time, consumers show no evidence of learning. We discuss the implications of the findings for marketers, consumers, platforms, and regulators.
When Money Mutes Mission: Platform Monetarization Policy and the Supply of Sustainability Content
Abstract
Digital content plays a crucial role in promoting sustainability in today’s environments. This study examines whether and how platform monetization policies influence the supply of sustainability-related content. We exploit a natural experiment induced by YouTube’s policy in 2017 requiring channels to have a minimum of 10,000 lifetime views to qualify for monetization, which resulted in the demonetization of many smaller channels. We employ a regression discontinuity design to identify the causal impact of demonetization on the content supply of creators. Contrary to conventional expectations, we find that demonetization does not uniformly suppress content production. On average, creators reduce their content supply after losing monetization; however, those with a stronger commitment to sustainability significantly increase their content supply. This heterogeneous response indicates that the removal of extrinsic incentives can encourage intrinsically motivated prosocial content creation. Moreover, we find that demonetization alters the distribution of voices on the platform: it disproportionately suppresses content supply from creators with less polarized views. Our results provide new insights into the unintended consequences of platform monetization policy and offer implications for digital platforms and policymakers seeking to encourage sustainability-related content.
From Aversion to Activation: The Impact of AI-Posted Content on User Contribution Quantity and Quality (with Peng Luo, Ying Chen, Banggang Wu, and Yongqiang Li)
Major Revision, Production and Operations Management
Abstract
Social media platforms increasingly deploy AI-operated accounts that publicly post content alongside human contributors to seed conversations and stimulate engagement. However, such visible AI participation may also undermine authenticity and trust, potentially dampening user activity. This research studies the impact of AI-posted content on subsequent user contributions in a large Chinese product-recommendation community. Using a synthetic difference-in-difference design, we estimate the causal effect of AI-posted content on both the volume and quality of subsequent user contributions. We find exposure to AI-posted content increases subsequent user contribution volume and improves multiple dimensions of content quality, including length, readability, sentiment intensity, and rationality. Furthermore, we show that the primary mechanism is a disclosure effect, i.e., the knowledge that content originated from AI, rather than a content effect driven by the linguistic features of the AI-posted content. These findings reveal that algorithm aversion can manifest as mobilized participation, as users engage to correct, complement, or contest AI input. We extend research on generative AI from private, assistive tools to public, autonomous contributors and inform platform policies on AI deployment and disclosure.