The amplification of demand variation in a supply chain network (SCN) is a well-known phenomenon called the bullwhip effect. This effect generates a large volume of inefficiencies as it moves a greater number of units than necessary, increases stock and generates stock-outs. There are two different approaches for avoiding and/or limiting this detrimental phenomenon that have received attention in the literature: Collaboration and information sharing in SCNs on one hand, and the adoption of smoothing replenishment rules on the other. The effectiveness of both approaches have been often analyzed only for "serial linked" SCNs, which is a supply network structure rarely found in real-life. In order to give an insight of how these techniques would perform in more generic SCNs, a divergent SCN has been benchmarked against the classical serial SCN. The computational experience carried out show that the bullwhip effect can be considerably reduced by collaboration or the smoothing replenishment rules in divergent SCNs, but it always performs worse than the serial SCN due to its inherent complexity. (C) 2014 Elsevier Ltd. All rights reserved.

On bullwhip-limiting strategies in divergent supply chain networks

CANNELLA, SALVATORE;
2014

Abstract

The amplification of demand variation in a supply chain network (SCN) is a well-known phenomenon called the bullwhip effect. This effect generates a large volume of inefficiencies as it moves a greater number of units than necessary, increases stock and generates stock-outs. There are two different approaches for avoiding and/or limiting this detrimental phenomenon that have received attention in the literature: Collaboration and information sharing in SCNs on one hand, and the adoption of smoothing replenishment rules on the other. The effectiveness of both approaches have been often analyzed only for "serial linked" SCNs, which is a supply network structure rarely found in real-life. In order to give an insight of how these techniques would perform in more generic SCNs, a divergent SCN has been benchmarked against the classical serial SCN. The computational experience carried out show that the bullwhip effect can be considerably reduced by collaboration or the smoothing replenishment rules in divergent SCNs, but it always performs worse than the serial SCN due to its inherent complexity. (C) 2014 Elsevier Ltd. All rights reserved.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11769/243872
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