Dynamic Capacity Allocation to Customers Who Remember Past Service

Daniel Adelman () and Adam J. Mersereau ()
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Daniel Adelman: Booth School of Business, The University of Chicago, Chicago, Illinois 60637
Adam J. Mersereau: Kenan-Flagler Business School, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599

Management Science, 2013, vol. 59, issue 3, 592-612

Abstract: We study the problem faced by a supplier deciding how to dynamically allocate limited capacity among a portfolio of customers who remember the fill rates provided to them in the past. A customer's order quantity is positively correlated with past fill rates. Customers differ from one another in their contribution margins, their sensitivities to the past, and in their demand volatilities. By analyzing and comparing policies that ignore goodwill with ones that account for it, we investigate when and how customer memory effects impact supplier profits. We develop an approximate dynamic programming policy that dynamically rationalizes the fill rates the firm provides to each customer. This policy achieves higher rewards than margin-greedy and Lagrangian policies and yields insights into how a supplier can effectively manage customer memories to its advantage. This paper was accepted by Martin Lariviere, operations management.

Keywords: dynamic programming; approximate; behavioral operations; customer relationship management; capacity allocation (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (27)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:59:y:2013:i:3:p:592-612

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