I am a Ph.D. student at London Business School, Management Science & Operations department. My research focuses on the design of pricing and matching systems for service platforms within the gig economy. Through my research, I aim to: (i) design computationally efficient and practical market algorithms, and (ii) improve social welfare and equity of market outcomes. I value maintaining strong connections with the industry and adopting an application-oriented research style. I believe that understanding real-world issues can lead to impactful new theories.
I am on the academic job market for the 2023-2024 academic year.
Contact
A. Ömer Sarıtaç
London Business School
Regents Park
London NW1 4SA, UK
osaritac@london.edu
Research
Centralized versus Decentralized Pricing Controls for Dynamic Matching Platforms, Aouad, S., and Yan, Working Paper (2023) [code]
Appeared in The 24th ACM Conference on Economics and Computation (EC), 2023
Dynamic Stochastic Matching Under Limited Time, Aouad and S., Operations Research (2022) [code]
Appeared in The 21st ACM Conference on Economics and Computation (EC), 2020
Online Contextual Influence Maximization with Costly Observations, S., Karakurt, and Tekin, IEEE Trans. Signal Inf. Process. over Networks (2019) [code]
Combinatorial multi-armed bandit problem with probabilistically triggered arms: A case with bounded regret, S., and Tekin, Working Paper (2018)
Accepted in the IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2017
Work in Progress
Pricing and Matching in a Decentralized Spatial Market (with Ali Aouad and Anatolii Prokhorchuk)
-In collaboration with Bolt, we study a novel decentralized pricing scheme using a model reflecting driver spatial distribution, highlighting the balance between competitive pricing and efficient pick-up times.
The Competitive Dynamics of Diverse Pricing Algorithms that Learn (with Ali Aouad and Arnoud V. den Boer)
-We study whether technological differences in pricing algorithms may explain the empirically observed supra-competitive prices and price dispersion in competitive markets.
Competition Between Platforms in the Gig Economy under Decentralized Pricing
-Based on intriguing data from Bolt, in a competitive gig economy landscape, this study aims to understand suppliers' pricing across platforms with differing pricing decentralization (early stages).
2023 INFORMS Annual Conference Presentation Information
Award Session: SB74-Centralized Versus Decentralized Pricing Controls for Dynamic Matching Markets. Date: 10/15/23. Time: 10:45 AM. Location: Phoenix Convention Center-West 106C
SC14-Centralized Versus Decentralized Pricing Controls for Dynamic Matching Markets. Date: 10/15/23. Time: 12:45 PM. Location: Phoenix Convention Center-North 125B