Abstract
In the last twenty years companies have always paid great attention on managing demand variability. Demand fluctuations are due to several reasons: quick changes in the final customer’s preferences and taste are a common cause of demand variability (e.g., in the fashion industry demand for a given color can change dramatically from year to year). Marketing activities may also lead demand to suddenly change e.g., when promotional activities are conducted due to the high elasticity of demand to price. Competitors can also be a source of variability, since their behavior can influence how the demand distributes on each single company serving a specific market. The supply chain structure is also a significant cause of demand unsteadiness: the bullwhip effect (Lee et al. 1997) is a common phenomenon in different industrial contexts, leading to an increase in the variability of the demand over supply chain stages.
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- 1.
The Friedman test is the nonparametric equivalent of a one-sample repeated measures design or a two-way analysis of variance with one observation per cell. Friedman tests the null hypothesis that k related variables come from the same population. For each case, the k variables are ranked from 1 to k. The test statistic is based on these ranks.
- 2.
For space sake we omit all statistical analyses. All contingencies have been evaluated at daily level since this was the most detailed level available.
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Bartezzaghi, E., Kalchschmidt, M. (2011). The Impact of Aggregation Level on Lumpy Demand Management. In: Altay, N., Litteral, L. (eds) Service Parts Management. Springer, London. https://doi.org/10.1007/978-0-85729-039-7_4
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