Although in-feed advertising is popular on mainstream platforms, academic research on it is limited. Platforms typically deliver organic content through two methods: subscription by users or recommendation by artificial intelligence. However, little is known about the ad performance between these two channels. This research examines how the performance of in-feed ads, regarding click-through rate (CTR) and conversion rate (CR), differs between subscription and recommendation channels and whether these effects are mediated by ad intrusiveness and moderated by ad attributes. Two ad attributes are investigated: ad appeal (informational vs. emotional) and ad link (direct vs. indirect). Study 1 finds that the recommendation channel generates higher CTRs but lower CRs than the subscription channel, and these effects are amplified by informational ad appeal and direct ad links. Study 2 explores channel differences, revealing that the recommendation channel yields less source credibility and content control, reducing consumer engagement with organic content. Studies 3 and 4 validate the mediating role of ad intrusiveness and rule out ad recognition as an alternative explanation. Study 5 uses eye-tracking technology to show that the recommendation channel has lower content engagement, lower ad intrusiveness, and greater ad interest.
3910 2183
KK 706
Ph.D. in Business Administration (Marketing), University of Illinois, Urbana-Champaign, 2019
M.Phil. in Marketing, Lingnan University, 2014
Bachelor in Business Administration, Xi’an Jiaotong University, 2012
Mengzhou (Austin) Zhuang joined the University of Hong Kong in 2019, after receiving his Ph.D. in Business Administration (Marketing) from University of Illinois, Urbana-Champaign. Before that he received his M.Phil. in Marketing from Lingnan University, and Bachelor degrees in Business Administration from Xi’an Jiaotong University.
His research interests lie in online advertising and multi-channel marketing strategy. His work primarily focuses on understanding the strategic decisions of multi-channel retailers, online advertisers, retailing platforms, and consumers.
Multi-channel strategy, online advertising, pricing, Bayesian statistics, machine learning.
- Yiyi Li, Mengzhou Zhuang and Eric (Er) Fang. Multichannel Effects of Mobile Infeed Advertising. Journal of Marketing. Forthcoming.
- Beibei Dong, Mengzhou Zhuang, Eric (Er) Fang, and Minxue Huang (2023). Tales of Two Channels: Digital Advertising Performance Between AI Recommendation and User Subscription Channels. Journal of Marketing, 88(2), 141-162, 2024. (Equal authorship)
- Er Fang, Beibei Dong, Mengzhou Zhuang, and Fengyan Cai (2023). “We Earned the Coupon Together”: The Missing Link of Experience Cocreation in Shared Coupons. Journal of Marketing, 87(3), 451–471, 2023. (Equal authorship)
- Mengzhou Zhuang, Eric (Er) Fang, Jongkuk Lee, and Xiaoling Li (2021). The Effects of Price Rank on Clicks and Conversions in Product List Advertising on Online Retail Platforms. Information Systems Research, 32(4), 1412-1430.
- Mengzhou Zhuang, Geng Cui, and Ling Peng (2018). Manufactured Opinions: The Effect of Manipulating Online Product Reviews. Journal of Business Research, 87, 24-35.