It has been shown that, at least in simulated scenarios of variability decomposition in size and frequency, the way these components are measured largely determines the shape of their relationships. This study aims to build on this specific finding and tests how these measures of variability components behave on real data. Moreover, getting advantage of the type of available data, several models are setup to assess amplification on such variability components, and to evaluate the impact of the product type on both: amplification and component variability behaviors. We do this by performing model assessment with the traditional un-weighted C.V. measure, and then replicating the same evaluation with the recently proposed ADV measure.
Monsreal, M. M., Royo, J. A., & Lambán, M. P. (2014). Order variability decomposition: A new variability measure on real data. Journal of Applied Research and Technology, 12(4), 695–703. https://doi.org/10.1016/S1665-6423(14)70086-0