My research lies at the intersection of revenue management, pricing, and matching markets, with a focus on how firms can design pricing and allocation strategies in environments shaped by uncertainty, heterogeneity, and large-scale data. Across my projects, I develop theory-driven models that provide both structural insights and implementable solutions, aiming to bridge rigor and managerial relevance.
This paper studies the optimal dynamic pricing of split-stay products, where a trip is divided between two accommodations. Using a dynamic programming framework with linear random utility models, I derive the structure of optimal pricing policies and show that split stays play an unexpected inventory-balancing role. They are used primarily in the mid-range of the selling horizon, when the need to rebalance capacity is most acute. The results highlight that split stays are not only a product innovation but also a powerful lever for revenue and inventory management.
Major Revision at Management Science
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Presale vouchers are widely used in the hospitality industry during promotional campaigns. I model voucher redemption as a random maximum network flow problem to capture the joint capacity constraints between voucher and market buyers. The analysis provides guidelines for voucher pricing, redemption policies, and inventory allocation, showing when vouchers can enhance both revenue and customer engagement.
This project develops a linear programming framework for frictional matching markets with heterogeneous agents and additive search costs. The formulation connects the matching literature to classical optimal assignment problems, allowing us to prove equilibrium properties such as positive assortative matching. Numerical experiments explore how search frictions affect social welfare and suggest policy tools, such as unemployment benefits, to mitigate inefficiencies.
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LIBOR Transition into SOFR (2019β2020) β Modeled interest rate term structures using Vasicek and Hull-White models and applied ARIMA/GARCH methods for time series analysis. Selected as a representative project at the 2020 SOFR Summit.
Undergraduate Thesis: Extensions of the Black-Scholes Model (2018β2019) β Developed and simulated option pricing models including Black-Scholes, Heston, and GARCH, applying Monte Carlo methods for equity derivative pricing. Completed as senior thesis at the University of Notre Dame.