Publications:
  • Bargaining between Collaborators of a Stochastic Project. RAND Journal of Economics, forthcoming. [Link] 
Summary: The paper studies a continuous-time bilateral bargaining model. With stochastic payoffs and outside options, asymmetric bargaining power causes players to reach an agreement earlier than what is optimal. As a result, a more balanced bargaining power can increase the length of bargaining and benefit all parties.

  • How Does Competition Affect Exploration vs. Exploitation? A Tale of Two Recommendation Algorithms (with H. Henry Cao, Liye Ma, and Baohong Sun). Management Science, forthcoming. ​[Link] [SSRN]
Summary: We study dynamic competition between two content recommendation algorithms fighting for the attention of strategic multi-homing users. We show that when users are less patient than firms, the optimal algorithm for competing firms should focus more on exploitation and less on exploration than the optimal algorithm for a monopoly. We then discuss firms' incentives to upgrade from myopic algorithms (e.g., supervised learning based) to forward-looking algorithms (e.g., reinforcement learning based), and the effect of such technological upgrade on industry profit and consumer welfare.

Summary: We model a consumer's dynamic purchase and repurchase decisions for a product that is both a search good and an experience good. That is, the consumer can acquire information about the product both before owning the product and after owning the product. We find that a higher speed of learning through experience leads to more initial purchases but fewer subsequent repurchases, whereas a higher speed of learning through search leads to fewer initial purchases but more subsequent repurchases.

Summary: Firms have to reposition their products periodically because consumer preferences change over time. We study a continuous-time game of horizontal positioning where consumers' ideal location evolves over time and two firms decide when to reposition and where to position to. We find that competing firms reposition less frequently than what is socially optimal and than what collusion (or merger) would imply. We also find more differentiation under collusion (or merger) than under competition, which is the opposite of the prediction from static models of differentiation.

  • List Price and Discount in A Stochastic Selling Process. Marketing Science, 2021, 40(2).​​  [Link] [SSRN]
Summary: In many B2B markets, sellers never sell at their list prices. This paper provides a rational explanation for such a phenomenon. By studying a continuous-time game between one buyer and one seller with sequential information acquisition and repeated offers, I show that a self-imposed price ceiling, though never binding in equilibrium, facilitates trade by reducing the buyer's hold-up problem. The model also provides predictions for AI-powered e-commerce where the seller predicts each buyer's purchase intention in real time during a browsing session and interferes with personalized discounts.

Working Papers:
  •  Targeted Advertising: Strategic Mistargeting and Personal Data Opt-Out. Revise and Resumbit, Marketing Science (with Jiwoong Shin and Jungju Yu). [Link]
Summary: We study the optimal targeting strategy of an advertiser and its implications on consumer's data privacy choices, which, in turn, affect the firm's targeting accuracy. When consumers have uncertainties about their preferences, an ad targeted to a consumer carries an implicit message: the algorithm predicts that the product fits her preferences. This implicit recommendation influences the consumer's purchase decision but also introduces misaligned incentives. As the accuracy improves, consumer inference from targeted ads becomes stronger, but so does the advertiser's incentive to exploit it to affect the consumer's decision.​

Summary: The paper considers a model of choice deferral in which individuals have to strategically decide whether to defer choice when information gathering is interrupted, taking into account the current available information, and when they will be able to resume gathering information. The paper also considers optimal pricing and shows how pricing should respond to the length of consumer browsing sessions and gaps between browsing sessions.

  • To Each Their Own: Personalized Product Positioning and Competition (with Jinzhao Du). [Link]
Summary: We study competition between two firms that offer personalized product positioning to consumers with horizontally distributed tastes. Firms have private, imperfect signals of each consumer's ideal location and offer each consumer a personalized positioning and price depending on that signal, without observing the competing firm's personalized offering. We characterize the equilibrium personalization strategy and examine how the accuracies of firms' signals affect equilibrium strategy, profits, and consumer welfare.
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  • Label Informativeness and Price Sensitivity for Cigarettes. Reject and resubmit, Journal of Marketing Research. [Available upon request]
Summary: In 2009, the U.S. banned tobacco companies from using descriptors such as "regular", "light", "ultralight" on cigarette packages. Companies continue to sell theses products by renaming them using color codes such as "red", "blue", and "silver". I find that after removing the informative descriptors, smokers are less sensitive to prices when choosing among cigarette products, which suggest that smokers perceive products to be more differentiated after the regulation.
         
Work in Progress​
  • Allocation of Attention in Observational Learning (with Harry Zihao Zhou).
  • Making the Right Mistakes: An Algorithmic Learning and Decision-Making Calculus (with Kinshuk Jerath).