In this article, we discuss ways of actively influencing product returns and we review data-driven methods for forecasting return flows that exploit the fact that future returns are a function of past sales. In particular we assess the value of return forecasting at an operational level, specifically for inventory control. We conclude with implications for supply chain management.
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Paper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number
316.
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
M.P. de Brito & S.D.P. Flapper & R. Dekker, 2002.
"Reverse logistics,"
Econometric Institute Report
272, Erasmus University Rotterdam, Econometric Institute.
[Downloadable!]
Other versions:
Brito, M.P. de & Flapper, S.D.P. & Dekker, R., 2002.
"Reverse logistics,"
Econometric Institute Report
EI 2002-21 Revision_Date:, Erasmus University Rotterdam, Econometric Institute.
[Downloadable!]
Laan, E.A. van der & Kiesmueller, G.P., 2001.
"An Inventory Model with Dependent Product Demands and Returns,"
Research Paper
ERS-2001-16-LIS Revision_, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.
[Downloadable!]
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