The bullwhip effect is defined as the distortion\r\nof demand information as one moves upstream in the\r\nsupply chain, causing severe inefficiencies in the whole\r\nsupply chain. Although extensive research has been\r\nconductedtostudythecausesofthebullwhipeffectand\r\nseekmitigationsolutionswithrespecttoseveraldemand\r\nprocesses, less attention has been devoted to the impact\r\nofseasonaldemandinmultiechelonsupplychains.This\r\npaperconsidersasimulationapproachtostudytheeffect\r\nof demand seasonality on the bullwhip effect and\r\ninventory stability in a fourechelon supply chain that\r\nadopts a base stock ordering policy with a moving\r\naverage method. The results show that high seasonality\r\nlevelsreducethebullwhipeffectratio,inventoryvariance\r\nratio, and average fill rate to a great extent; especially\r\nwhen the demand noise is low. In contrast, all the\r\nperformance measures become less sensitive to the\r\nseasonality level when the noise is high. This\r\nperformance indicates that using the ratios to measure\r\nseasonalsupplychaindynamicsismisleading,andthatit\r\nisbettertodirectlyusethevariance(withoutdividingby\r\nthe demand variance) as the estimates for the bullwhip\r\neffect and inventory performance. The results alsoshow\r\nthatthesupplychainperformancesarehighlysensitiveto\r\nforecastingandsafetystockparameters,regardlessofthe\r\nseasonalitylevel.Furthermore,theimpactofinformation\r\nsharing quantification shows that all the performance\r\nmeasures are improved regardless of demand\r\nseasonality.Withinformationsharing,thebullwhipeffect\r\nandinventoryvarianceratiosareconsistentwithaverage\r\nfillrateresults.
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