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Title: Dynamic Pricing and Matching for Two-Sided Queues
Motivated by applications from gig economy and online marketplaces, we study a two-sided queueing system under joint pricing and matching controls. The queueing system is modeled by a bipartite graph, where the vertices represent customer or server types and the edges represent compatible customer-server pairs. We propose a threshold-based two-price policy and queue length-based maximum-weight matching policy and show that it achieves a near-optimal profit. We study the system under the large-scale regime, wherein the arrival rates are scaled up, and under the large-market regime, wherein both the arrival rates and numbers of customer and server types increase. We show that two-price policy is a primary driver for optimality in the large-scale regime. We demonstrate the advantage of maximum-weight matching with respect to the number of customer and server types. Concurrently, we show that the interplay of pricing and matching is crucial for optimality in the large-market regime.  more » « less
Award ID(s):
2145661
NSF-PAR ID:
10482722
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
INFORMS
Date Published:
Journal Name:
Operations Research
Volume:
71
Issue:
1
ISSN:
0030-364X
Page Range / eLocation ID:
83 to 100
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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