Selecting and Using an Adequate Disaggregation Level in Time Series Forecasting: A Study Case in a Subscription Business Model Company through the Analytic Hierarchy Process
DOI:
https://doi.org/10.46661/revmetodoscuanteconempresa.2220Keywords:
Toma de decisiones multicriterio, análisis jerárquico, agregación de series temporales, pronósticos de series temporales, empresas de suscripciónAbstract
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.Downloads
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