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Yunru Han PhD


Division: Decision, Risk & Operations

Advisers:

  • Fangruo Chen

YHan14@gsb.columbia.edu

4K Uris


ABOUT ME

Education

BS, Mathematics & Physics (Academic Talent Program), Tsinghua University (China), 2009

Research in progress

Demand Learning and Market Entry of an Online Retail Platform with Third-Party Sellers (Work in progress with Fangruo Chen): This paper studies the merchandising ("entry") strategies for an online retail platform (Platform Owner or "PO") through demand learning from the third-party sellers (Independent Sellers or "IS") operating in their marketplace. The PO (e.g. Amazon.com) could make profits as both a retailer by owning and selling products, and an intermediary by collecting commissions and fees from other sellers on the platform, i.e. the IS. The PO’s access to the IS’s transaction history provides a great advantage for the PO to discover profitable products to carry and sell. The PO’s potential entry into a profitable market could lead to the IS’s strategic reactions, e.g. hiding their best-selling items. We propose a Stackelberg game of incomplete information between the PO and a single IS, and the equilibrium results address the following questions: 1)The PO’s strategic choice between retaining and renouncing the "entry" option; 2) The PO’s optimal entry policies (threshold and timing) based on dynamic demand learning; 3) The IS’s optimal pricing policies, taking into account the PO’s learning and entry policies.

Research Interests

  • E-commerce
  • Platform-based Business
  • Strategic Learning
  • Supply Chain Contracting
  • Data-driven Revenue Management
Division: 
Decision, Risk & Operations
Research Interests: 
E-commerce
Platform-based Business
Strategic Learning
Supply Chain Contracting
Data-driven Revenue Management
Advisers: 
Fangruo Chen
Research in Progress: 
Demand Learning and Market Entry of an Online Retail Platform with Third-Party Sellers (Work in progress with Fangruo Chen): This paper studies the merchandising ("entry") strategies for an online retail platform (Platform Owner or "PO") through demand learning from the third-party sellers (Independent Sellers or "IS") operating in their marketplace. The PO (e.g. Amazon.com) could make profits as both a retailer by owning and selling products, and an intermediary by collecting commissions and fees from other sellers on the platform, i.e. the IS. The PO’s access to the IS’s transaction history provides a great advantage for the PO to discover profitable products to carry and sell. The PO’s potential entry into a profitable market could lead to the IS’s strategic reactions, e.g. hiding their best-selling items. We propose a Stackelberg game of incomplete information between the PO and a single IS, and the equilibrium results address the following questions: 1)The PO’s strategic choice between retaining and renouncing the "entry" option; 2) The PO’s optimal entry policies (threshold and timing) based on dynamic demand learning; 3) The IS’s optimal pricing policies, taking into account the PO’s learning and entry policies.
Education: 
degree: 
BS
major: 
Mathematics & Physics (Academic Talent Program)
school: 
Tsinghua University (China)
year: 
2 009
contact info: 
Office room #: 
4K
personal website: 
awards: 
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