5 Conclusions

Many economical decisions are deduced from historical databases, e.g. sales history. In this paper, we have shown that the best decision for the newsboy problem depends heavily on the choice of the dispersion measure. The "Scarf's rule" follows only when assuming an exact knowledge of the variance, while another strategy follows when assuming an exact knowledge of the intermeans parameter $\delta$, defined as:

$$\delta \doteq\theta \left(1-\theta \right)\left(\xi ^{u}-\xi ^{o}\right)$$

Therefore any additional knowledge that can be used leads to a better decision and have therefore an information value. We have shown that informations concerning the best method to summarize the dispersion can be more valuable than other informations concerning the shape of the distribution.

In any case, the exact identification of reduced parameters concerning the demand models seems to be questionable, and a description using larger families of pdfs with confidence intervals such as $\mathcal{F}\left(\mu\pm\Delta\mu,\sigma\pm\Delta\sigma\right)$ or $\mathcal{F}\left(\mu\pm\Delta\mu,\delta\pm\Delta\delta\right)$ seems to be more robust when describing problems relative to the supply chain.