Abstract
In this study the author goes through with the analysis of a cost model developed for Integrated Logistic Support (ILS) activities. By means of ANOVA the evaluation of impact and interaction among cost drivers is done. The predominant importance of organizational factors compared to technical ones is definitely demonstrated. Moreover the paper provides researcher and practitioners with useful information to improve the cost model as well as for budgeting and financial planning of ILS activities.
Highlights
A cost model is a mathematical algorithm or parametric equation that converts input data into the cost of a product, service or project
This study has discussed an application of the Analysis of Variance (ANOVA) and Taguchi method for investigating the effects of cost drivers on the cost model for the Integrated Logistic Support (ILS) activities
From the analysis of the results using the ANOVA and Taguchi’s optimization method, the following can be concluded from the present study:
Summary
A cost model is a mathematical algorithm or parametric equation that converts input data into the cost of a product, service or project. A cost model most often involves synthesizing data from a number of sources and a persistent methodological problem is how to deal with the input uncertainty. Many authors use a Monte Carlo method (You et al, 2009; Yang, 2011; Loizou and French, 2012) to propagate the uncertainty from the input data to the result variables. This study aims to complete the analysis of a specific cost model firstly proposed by the author and evaluated through the Monte Carlo method (Nenni, 2013a). The second contribution from Nenni (2013b) analyses more in depth the cost model through the Monte Carlo method in order to manage the uncertainty of the model. Maria Elena Nenni / American Journal of Applied Sciences 10 (12): 1570-1574, 2013
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