Jinzhao Du
Prof. Jinzhao DU
市场学
BBA Deputy Programme Director and Admissions Tutor
Assistant Professor

3917 4478

KK 708

Academic & Professional Qualification
  • Ph.D. in Marketing, Duke University, 2018
  • B.A. in Economics, Tsinghua University, 2012
Biography

Jinzhao Du’s research investigates platform-based marketing. His current work studies media platforms and matching platforms. His research on media platforms focuses on the strategic interactions among multiple players including publishers, consumers, advertisers, content suppliers, and news aggregators, and their implications on media platforms’ decisions such as pricing, content provision, and collaboration with news aggregators. His work on matching platforms focuses on how information design, strategic pricing, and AI development can improve matching outcomes, and their implications for firm strategies, consumer welfare, and regulators’ policymaking. He uses game-theoretic models to enhance understanding of new phenomena and practices in this growing field.

Jinzhao Du receives his Ph.D. in marketing from the Fuqua School of Business at Duke University and  B.A. in Economics from the School of Economics and Management at Tsinghua University.

Teaching
  • Pricing Strategies and Tactics (MSMK 7031)
  • Pricing Strategies (MKTG3527)
  • Introduction to Marketing (MKTG2501)
Research Interest

Platform-based marketing, Multi-sided media market, Matching, AI impact, Applied game theory.

Selected Publications
  • Yuxin Chen, Jinzhao Du, and Ying Lei (2024), “The Interactions of Customer Reviews and Price and Their Dual Roles in Conveying Quality Information,” Marketing Science, Forthcoming.
  • Wilfred Amaldoss, Jinzhao Du, and Woochoel Shin (2024), “Pricing Strategy of Competing Media Platforms,” Marketing Science, 43(3), 488-505.
  • Wilfred Amaldoss and Jinzhao Du (2023), “How can Publishers Collaborate and Compete with News Aggregators?” Journal of Marketing Research, 60(6), 1114-1134.
  • Jinzhao Du and Ying Lei (2022), “Information Design of Matching Platforms when User Preferences are Bidimensional,” Production and Operations Management, 31(8), 3320-3336.
  • Wilfred Amaldoss, Jinzhao Du, and Woochoel Shin (2021), “Media Platforms’ Content Provision Strategies and Sources of Profits,” Marketing Science, 40(3), 527-547.
Recent Publications
用户偏好具有二重维度时匹配平台的信息设计

为用户提供主动匹配搭建平台的企业在提高匹配效率和保证匹配质量方面面临着巨大的挑战。本文研究了当用户从匹配的垂直属性(即质量)及其水平属性(即异质性匹配)中获得效用时,信息设计如何用于改善匹配结果。我们考虑一个博弈论模型,其中互相竞争的发送者向互相竞争的接收者提出匹配请求,并且两侧的用户在水平和垂直方向上都有差异。我们首先证明用户对垂直属性的偏好会加剧竞争并损害匹配效率,并且为了避免竞争,发送者可能会从近距离接收者切换到远距离接收者,即便对匹配的水平接近度更加看中。其次,我们研究了四种信息设计,每种设计隐去来自市场一侧的一种类型的信息。隐去任何一侧的垂直信息的设计增加了匹配的数量,这其中隐去接收者信息的改进更大。相比之下,隐去任何一侧水平信息的设计可能导致所有请求都集中在一个接收者上,并导致最严重的匹配失败。第三,匹配数量的增加是以牺牲某些用户福利为代价的,因为隐去一侧的垂直信息不仅会伤害双侧的高质量用户,也会伤害另一侧的低质量用户。尽管在某些条件下隐去一侧的水平信息可能会增加匹配量,但隐去一侧的垂直信息的设计可以做到帕累托改进。第四,在配过程中用户的自行策略定价不仅重新分配了用户福利,而且纠正了匹配失真。最后,与没有用户定价的结果对比,当用户可以策略定价时,平台隐去一侧的纵向信息可以使另一侧的所有用户受益,而隐去一侧的横向信息可以使同一侧的所有用户受益。

媒体平台的内容提供策略及利润来源

一些媒体平台从消费者及广告商双方赚取利润(例如Spotify、Hulu),而另一些平台的利润则单方面来自广告商(例如Jango、Tubi)或消费者(例如Tidal、Netflix)。因此,根据如何将有限的版面空间分配给内容和广告,媒体平台的策略不尽相同。在本文中,我们考虑到多边媒体市场的跨边网络相应以及内容提供商的竞争特性,考察媒体平台的内容提供策略及其对媒体平台和内容供应商在利润方面的影响。为了帮助分析,我们建立了一个媒体平台与内容供应商、消费者和广告商三方互动的模型。首先,我们关于完全竞争的内容市场的分析表明,尽管消费者对内容的渴望可以提高其支付意愿,却同时可以伤害到媒体平台的利润。其次,和人们的预期相反,平台的利润可以因获取内容成本的提高而增长。第三,当平台使用付费内容加广告的策略时,广告商对于触达消费者的意愿会降低垄断市场的内容供应商的利润。第四,一个垄断市场的内容供应商无法从榨取竞争平台的全部利润。此外,互相竞争的内容供应商可能会收取比垄断市场的内容供应商更高的价格。最后,我们阐述了内容市场的竞争特性如何影响平台对于无广告策略的选择。

连结资讯科技与金融:罗晔博士

罗博士不仅是一名数学家,他同时亦是一名热衷于把机器学习理论应用在商业用途上的学者,以及一位经验丰富的商业顾问。

平台攻略:杜金钊博士

杜博士是一位主力研究平台公司的市场学学者。热衷于学习新的营销趋势的他期待着与同学们共同创造知识。