Seminar: Paola Martin

Monday, January 17, 2022 11:00 am - 11:00 am EST (GMT -05:00)

Trade Credit and Sales Data Visibility

Paola Martin

McCombs School of Business
University of Texas at Austin



In many wholesale-price-based trade finance transactions, the supplier does not observe the retailer's post-sales assets. This information can be learned if the retailer shares Point-of-Sales (POS) data with the supplier. Alternatively, the supplier may verify sales, which is costly, thus presenting a decision problem. The potential benefit of POS data sharing on sales and inventory costs without trade credit has been explored in the literature. However, its interaction with trade finance remains largely unexplored.  In particular, we are interested in determining whether the supplier benefits from observing POS data from a trade finance perspective, when the cost of acquiring such information is zero. We formulate a game theoretic leader-follower model and derive equilibrium actions of the supplier and the retailer with or without POS data exchange. We identify a range of problem primitives within which the supplier benefits from not observing POS data. We also present numerical examples to tease out the impact of wholesale price, retailer's assets, and verification cost on POS data sharing. 

Biographical Sketch

Paola Martin is a PhD Candidate from the Information, Risk, and Operations Management Department at the University of Texas at Austin. Paola received her B.S. in Industrial & Systems Engineering from the University of Minnesota. Paola’s research focuses on supply chain finance and healthcare operations. She has studied ways in which firms can meet their capital needs through either crowdfunding or vendor financing, and she has looked at ways to improve the use of older-donor kidneys for transplantation. At the intersection of supply chain finance and healthcare operations, she has analyzed financial subsidy contracts to assist global health organizations procure the maximum number of vaccines for developing countries. Paola’s research utilizes multiple methodologies including game theory, optimization and data analytics.