Congestion-based leadtime quotation and pricing for revenue maximization with heterogeneous customers

Authors:
Barış Ata;Tava Lennon Olsen
Affiliations:
Kellogg School of Management, Northwestern University, Evanston, USA 60208;University of Auckland Business School, University of Auckland, Auckland, New Zealand
Venue:
Queueing Systems: Theory and Applications
Year:
2013

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Abstract

This paper studies a queuing model where two customer classes compete for a given resource and each customer is dynamically quoted a menu of price and leadtime pairs upon arrival. Customers select their preferred pairs from the menu and the server is obligated to meet the quoted leadtime. Customers have convex---concave delay costs. The firm does not have information on a given customer's type, so the offered menus must be incentive compatible. A menu quotation policy is given and proven to be asymptotically optimal under traditional large-capacity heavy-traffic scaling.