Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/113849
Authors: 
Alvarado Valencia, Jorge Andrés
García Buitrago, Javier Alexander
Year of Publication: 
2013
Citation: 
[Journal:] Revista de Métodos Cuantitativos para la Economía y la Empresa [ISSN:] 1886-516X [Volume:] 15 [Year:] 2013 [Pages:] 45-64
Abstract (Translated): 
Hierarchical aggregation/disaggregation of time series in order to make forecasts is a frequent challenge in business and econometric scenarios. This work presents a novel approach for selecting an adequate time series disaggregation level as a starting point for making forecasts. The methodology combines qualitative criteria - such as business resources and decision environment - and quantitative criteria - such as information quality and forecastability - in a multicriteria decision making task which is addressed through the analytic hierarchy process (AHP) technique. Results from a study case in a subscription business model company show the usefulness of combining AHP and time series forecasting techniques and the importance of multicriteria decision-making in the task of selecting an adequate aggregation/disaggregation level.
Subjects: 
multicriteria decision making
analytical hierarchy process
time series aggregation
time series forecasting
subscription business model
JEL: 
C44
M11
Document Type: 
Article

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