Xi LI
Prof. Xi LI
創新及資訊管理學
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 a 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
  • When Does It Pay to Invest in Pricing Algorithms, (with Xin Wang and Praveen K. Kopalle), Production and Operations Management, forthcoming.
  • Crowdfunding Success for Female Versus Male Entrepreneurs Depends on Whether a Consumer Versus Investor Decision Frame Is Salient, (with Huachao Gao, Xin Shane Wang and June Cotte), Journal of Marketing Research, 62(2), 274-293, 2025.
  • The Dark Side of Voluntary Data Sharing, (with Bingqing Li and Zhilin Yang), MIS Quarterly, 49(1), 155-178, 2025.
  • Endogenous Costs, Market Competition, and Disclosure, Marketing Science, 44(2), 374-389, 2025.
  • Is Personalized Pricing Profitable When Firms Can Differentiate? (with Xin Wang and Barrie R. Nault), Management Science, 70(7):4184-4199, 2024.
  • 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
價格的藝術:企業是如何使用數據「套路」消費者的?

2023年,比利時報紙Dernière Heure 爆料指出,網約車平臺Uber會根據用戶手機電量的不同向不同的使用者收取不同的價格。 [1] 具體而言,對於相同的一段旅程,如果你的手機剩餘電量有84%,Uber的收取的價格是16.6歐元;而如果你的剩餘電量只有12%,你的價格將是17.56歐元。 定價背後的邏輯顯而易見:如果你的手機快沒電了,你大概率是「等不起」的,只能無奈接受Uber的高價。

用演算法拿捏消費者? 「割韭菜」之前,請三思

網購時代,「舊用戶與狗不得享受」的優惠,往往讓忠實的消費者感到無奈。許多電商平台實施「一人一價」策略,甚至基於用戶的購買習慣和瀏覽記錄「看人下菜碟」,讓不同的消費者為同樣的商品支付不同的價格。此外,機票價格也不斷波動,越搜越貴已成常態。許多消費者發現,同一班機在不同時段價格差異龐大,甚至剛查看的票價,片刻後便上漲了。沒錯,你被演算法操控了──身為消費者,我們對商家的這些套路早已見怪不怪。

內地電商強攻下香港零售業如何自救

近期內地電商巨頭淘寶、京東、拼多多紛紛發力,將香港市場納入包郵區。過去港人需先通過中轉集運才能接收所訂貨品,相比之下,最新推出的一站式購物服務,自然大受歡迎。 無庸置疑,內地電商龍頭的搶灘行為必會影響本地零售業,讓早已低迷的銷情雪上加霜。這種趨勢下,本土零售業有什麼應對之道?筆者從以下3個角度建議業界如何破解困局。

Crowdfunding Success for Female Versus Male Entrepreneurs Depends on Whether a Consumer Versus Investor Decision Frame Is Salient

Ensuring equal access to entrepreneurship and startup funding for both female and male entrepreneurs is crucial for societal perceptions of justice and long-term prosperity. Previous research presents contrasting findings, with some studies indicating a male advantage and others suggesting a female advantage. This research reconciles these inconsistencies by identifying the decision frame as a moderator. Specifically, in crowdfunding contexts, a consumer decision frame leads to stronger reliance on communal evaluation norms, resulting in favoring female entrepreneurs who are perceived as more disadvantaged. Conversely, an investor decision frame leads to stronger reliance on exchange evaluation norms, resulting in favoring male entrepreneurs who are perceived as more determined/passionate. Based on this, the authors propose that the strategic use of an entrepreneur's profile, activating a specific evaluation norm, and showing crowdfunding dependence attenuate the differential support for female versus male entrepreneurs, resulting in equal support for both. Results from six studies using a multimethod design provide converging support for this framework. This research is the first to differentiate between and directly compare consumer and investor decision frames, advancing the related literature and offering valuable guidelines for entrepreneurs, funding platforms, and public policy makers.

Endogenous Costs, Market Competition, and Disclosure

Firms must often decide whether to disclose private information regarding their costs to other market participants. Although extant literature has explored firms’ incentives to disclose exogenous and uncertain costs, little is known about when their endogenous costs should be disclosed. This paper studies the cost-disclosure strategies of competing firms whose inputs are sourced from and endogenously priced by upstream suppliers. We find, first, that cost disclosure affects not only market competition but also the motivations of suppliers in setting their input prices. As such, firms can strategize their disclosure decisions to optimize their procurement costs. Second, we find that firms’ disclosure decisions vary depending on both the nature of the competition and the market structure at hand. That is, when competing firms source from the same supplier or compete on price, they never disclose their costs; in such a case, nondisclosure is strictly better for consumers and welfare compared with disclosure. When competing firms source from different suppliers and compete on quantity, they always disclose; in such a case, disclosure is strictly better for consumers and welfare compared with nondisclosure. We also find that whereas manufacturers’ disclosure incentives are misaligned with those of suppliers, they are largely aligned with the goal of maximizing channel profits. Together, our results underscore the distinct role that endogenous costs play in firms’ disclosure decisions.

The Dark Side of Voluntary Data Sharing

To balance the need for privacy and the benefits of big-data analytics, regulators around the world are giving consumers control over their data, allowing them to choose whether or not to voluntarily share their purchase history data with firms. Intuition suggests that voluntary data sharing only benefits consumers who can now choose to share their data only when it is profitable to do so. To investigate this argument, we build a model in which a monopolistic firm sells a repeatedly purchased product to consumers over two periods, and consumers decide whether or not to share their purchase history data with the firm, who can use it in the future to price discriminate against them. We find that, compared to when data collection is completely outlawed, voluntary data sharing can benefit the firm but at its consumers’ expense. Moreover, regulations that mandate firms to better protect consumer data against data breaches can backfire on consumers. Finally, we show that under voluntary data sharing, a firm’s ability to offer consumers a monetary incentive to share their data can improve profits without hurting consumers. Taken together, these findings underscore the surprising effects of voluntary data sharing and caution public policymakers of how certain data policies that, on the surface, seem purely beneficial can lead to unintended consequences.

Is Personalized Pricing Profitable When Firms Can Differentiate?

We consider the role of personalized pricing (PP) on product differentiation when PP is costly to implement. Using a stylized yet commonly used formulation, we find that when firms decide on positioning before deciding on PP implementation, PP implementation cost affects not only the amount of differentiation firms choose in their positioning, firm profits, consumer surplus, and social welfare, but also whether firms implement PP. When PP implementation cost is low, firms cannot help but to implement PP and engage in direct price competition. Moreover, firms implementing PP reduce their differentiation, further intensifying price competition, and are worse off. When PP implementation cost is moderate, firms position to reduce their differentiation to commit to not implementing PP, again aggravating price competition. In contrast, when PP implementation cost is higher, firms increase their differentiation due to the threat of PP but do not implement PP. As a result, the availability of PP improves firm profits, even though firms do not implement PP. However, if differentiation is restricted, then PP availability cannot improve firm profits. If an information seller sets the PP implementation cost, then it sets the cost low. Consequently, firms implement PP and are worse off. We also find that when firms decide whether to implement PP before deciding on positioning, they never implement PP. This is the case when PP implementation is complex, and differentiation can be affected by short-run advertising and promotion. Finally, we show that banning PP can benefit consumers when accounting for changes in firm positioning.

The Bright Side of Inequity Aversion

Modern consumers are concerned about not only their material payoff, but also the fairness of the transaction when making purchasing decisions. In this paper, we investigate how consumers’ inequity aversion affects a manufacturer who sources inputs from upstream suppliers. We find that, when the manufacturer sources from a single supplier or when consumers observe the manufacturer’s cost, inequity aversion hurts both the supplier’s and manufacturer’s profits. However, when the manufacturer sources from multiple suppliers and consumers do not observe the manufacturer’s cost, inequity aversion reduces both the suppliers’ and manufacturer’s margins, which significantly alleviates the double marginalization problem, increases consumer demand, and improves channel efficiency. As a result, inequity aversion benefits the suppliers, manufacturer, and consumers alike, leading to a “win–win–win” outcome. By comparing cases in which consumers observe and do not observe the manufacturer’s cost, we also find that, when faced with inequity-averse consumers, a manufacturer may find it optimal to withhold its cost information to help secure lower procurement costs from upstream suppliers.