Main Article Content
It has been shown that, at least in simulated scenarios of variability decomposition in size and frequency, the waythese components are measured largely determines the shape of their relationships. This study aims to build on thisspecific finding and tests how these measures of variability components behave on real data. Moreover, gettingadvantage of the type of available data, several models are setup to assess amplification on such variabilitycomponents, and to evaluate the impact of the product type on both: amplification and component variabilitybehaviors. We do this by performing model assessment with the traditional un-weighted C.V. measure, and thenreplicating the same evaluation with the recently proposed ADV measure.
How to Cite
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). https://doi.org/10.1016/S1665-6423(14)70086-0