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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/28109
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| Title: | Forecasting and Information Sharing in Supply Chains Under Quasi-ARMA Demand |
| Authors: | Giloni, Avi
Hurvich, Clifford
Seshadri, Sridhar |
| Keywords: | Supply Chain Management
Information Sharing
Time Series
ARMA
Invertibility |
| Issue Date: | 13-Jul-2009 |
| Series/Report no.: | SOR-2009-04 |
| Abstract: | In this paper, we revisit the problem of demand propagation in a
multi-stage supply chain in which the retailer observes ARMA demand. In
contrast to previous work, we show how each player constructs the order
based upon its best linear forecast of leadtime demand given its
available information. In order to characterize how demand propagates
through the supply chain we construct a new process which we call
quasi-ARMA or QUARMA. QUARMA is a generalization of the ARMA model. We
show that the typical player observes QUARMA demand and places orders
that are also QUARMA. Thus, the demand propagation model is
QUARMA-in-QUARMA-out. We study the value of information sharing between
adjacent players in the supply chain. We demonstrate that under certain
conditions information sharing can have unbounded bene¯ts. Our
analysis hence reverses and sharpens several previous results in the
literature involving information sharing and also opens up many
questions for future research. |
| URI: | http://hdl.handle.net/2451/28109 |
| Appears in Collections: | IOMS: Statistics Working Papers
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