Xi LI
Prof. Xi LI
市場學
Professor
Director, Asia Case Research Centre
Associate Director, Institute of Digital Economy and Innovation

3917 7271

KK 836

Academic & Professional Qualification
  • Ph.D., University of Toronto
  • M.Phil., HKUST
  • B.E., Tsinghua University
Biography

Xi Li is an Associate Professor of Marketing at the University of Hong Kong. He uses economics and machine learning methods to understand how information technologies such as artificial intelligence, recommender systems, data-driven algorithms, blockchain, and algorithmic pricing affect firms, consumers and the society, and how policymakers should regulate big data and protect consumer privacy.

Research Interest

Algorithms, big data and online marketplaces

Selected Publications
  • Is Personalized Pricing Profitable When Firms Can Differentiate? (with Xin Wang and Barrie R. Nault), Management Science, forthcoming.
  • When Does It Pay to Invest in Pricing Algorithms, (with Xin Wang and Praveen K. Kopalle), Production and Operations Management, forthcoming.
  • The Bright Side of Inequity Aversion, (with Xinlong Li), Management Science, 69(7):4210-4227, 2023.
  • Channel Coordination of Storable Goods, (with Krista J. Li and Xiong Yan), Marketing Science, 42(3):538-550, 2023.
  • Advance Selling in Marketing Channels, (with Krista J. Li), Journal of Marketing Research, 60(2), 371–387, 2023.
  • Beating the Algorithm: Consumer Manipulation, Personalized Pricing, and Big Data Management, (with Krista J. Li), Manufacturing & Service Operations Management, 25(1), 36-49, 2023.
  • Superior Knowledge, Price Discrimination, and Customer Inspection, (with Zibin Xu), Marketing Science, 41(6), 1029- 1182, 2022.
  • Strategic Inventories Under Supply Chain Competition, (with Yanzhi Li and Ying-Ju Chen), Manufacturing & Service Operations Management, 24(1), 77-90, 2022.
  • Contract Unobservability and Downstream Competition, (with Qian Liu), Manufacturing & Service Operations Management, 23(6), 1468-1482, 2021.
  • Audio Mining: The Role of Vocal Tone in Persuasion, (with Xin Wang, Shijie Lu, Mansur Khamitov, and Neil Bendle), Journal of Consumer Research, 48(2), 189-211, 2021.
  • Reviewing Experts’ Restraint from Extremes and Its Impact on Service Providers, (with Peter Nguyen, Xin Wang and June Cotte), Journal of Consumer Research, 47(5), 654-674, 2021.
  • Transparency of Behavior-Based Pricing, (with Krista J. Li and Xin Wang), Journal of Marketing Research, 57(1), 78-99, 2020.
  • Video Mining: Measuring Visual Information Using Automatic Methods, (with Mengze Shi and Xin Wang), International Journal of Research in Marketing, 36(2), 216-231, 2019.
  • Managing Consumer Deliberations in a Decentralized Distribution Channel, (with Yanzhi Li and Mengze Shi), Marketing Science, 38(1), 170-190, 2019.
  • Product and Pricing Decisions in Crowdfunding, (with Ming Hu and Mengze Shi), Marketing Science, 34(3), 331-345, 2015.
Awards and Honours
  • 2021 MSI Young Scholar
Recent Publications
擊敗算法:消費者操縱、個性化定價和大數據管理

現代企業利用大數據技術收集消費者數據,並對消費者進行個性化定價。與此同時,消費者可以利用各種手段篡改數據來誆騙公司,以獲取更優惠的價格。我們研究當消費者可以收集數據時企業應當如何收集消費者數據以及應否向消費者披露數據收集情況。研究考慮一個企業可以收集消費者數據以識別不同消費者的類型,並進行個性化定價,而消費者可以篡改數據。我們發現,當公司不向消費者披露數據收集範圍時,它會收集更多消費者數據;當公司披露數據收集範圍時,公司所收集的數據則會減少。消費者篡改數據可能對公司和消費者都不是一件好事。此外我們發現,公開數據收集範圍可以增加公司利潤、消費者盈餘及社會福利。 研究結果表明,公司應根據消費者操縱數據的成本和需求異質性,來調整數據收集範圍和價格。公共政策應要求公司披露其數據收集範圍,以增加消費者剩餘及社會福利。即使沒有強制披露數據的政策,企業也應該自願披露其數據收集範圍以增加利潤。此外,為消費者篡改數據提供便利最終可能會損害消費者和公司的利益。

以計算機科學的力量實現市場學數字化 – 李曦博士

香港大學的百年基業聲威遠播,再加上我們學院與亞太區的商業群體關係良好。在强强結合下,港大的市場學學者們在研究上將如虎添翼,並能更有效地把他們的研究和知識傳授給學生,繼而為社會培養更優秀的人才。

以計算機科學的力量實現市場學數字化 – 李曦博士

天生對周遭事物充滿好奇的李曦博士,自幼對市場營銷策略以及相關的經濟現象深感興趣。李博士非常欣赏港大經管學院卓越的研究水平,所以他最終在2021年7月以市場學副教授的身份加入我們港大經管學院的大家庭。