Of all oil products consumed by the Argentine Air Force (AAF), jet fuel is the resource with highest demand and at the end of the day the most expensive support item procured by the AAF. Accurate predictions of Argentine jet fuel prices are necessary to improve AAF financial and logistics planning. Multiple regression analysis is one such tool that can aid in accurately forecasting the amount required when procuring this valuable commodity. Using this methodology, we develop and illustrate a highly predictive model that has an adjusted R2 of 0.98 and an average percentage absolute error of 4%.
Salaverry, J.A. and White III, E.D. (2009), "Improving procurement through regression analysis: A case study of predicting argentine jet fuel prices", Journal of Public Procurement, Vol. 9 No. 1, pp. 1-16. https://doi.org/10.1108/JOPP-09-01-2009-B001Download as .RIS
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