Position Auctions with Endogenous Product Information: Why Live-Streaming Advertising Is Thriving

• 成果类型: Article; Early Access
• 署名作者: Chen, Yingtu; Gallego, Guillermo; Gao, Pin; Li, Yang
• 署名单位: Hong Kong University of Science & Technology; The Chinese University of Hong Kong, Shenzhen; The Chinese University of Hong Kong, Shenzhen; Western University (University of Western Ontario)
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2021.01299
• 发表日期: 2025
• 关键词: live-streaming; Position auction; Approximation algorithms; Information economics

摘要

Live-streaming advertising in e-commerce is soaring. Both Amazon and Alibaba have employed this novel marketing model to engage consumers by sequentially exhibiting different products through live-streaming videos. In this paper, we adopt a mechanism design framework to model live-streaming e-commerce as a position auction with endogenous provision of product information. We prove that finding the mechanism that simultaneously optimizes position allocation and information provision is NP-hard. Thus, we develop several approximation algorithms. Building on the connection to the order selection problem, our analysis establishes that heuristics relying solely on product information provision can achieve up to 66.9% of the optimal revenue in the worst case. In contrast, heuristics exploiting position allocation alone may result in arbitrarily large revenue losses. We attribute the efficacy of product information provision to its enhancement of the value of ad spots in position auctions. Our findings suggest that advertising that focuses on differentiating product information-as in live-streaming e-commerce-is more lucrative than conventional position-based sponsored search. This managerial insight remains valid when accommodating multiproduct purchases with dependency or accounting for random consumer attention spans.