Sales Forecasting in Retail Industry Based on Dynamic Regression Models

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2016

Autores

Pinho, JM (Autor) Outra; José Manuel Oliveira (Autor) FEP; Patrícia Ramos (Autor) FEUP

Ata de Conferência Internacional

Título: ADVANCES IN MANUFACTURING TECHNOLOGY XXX

Páginas: 483-488

14th International Conference on Manufacturing Research (ICMR)

Loughborough Univ, Loughborough, ENGLAND, SEP 06-08, 2016

Indexação

ISI Web of Knowledge - 1 Citação

Scopus - 1 Citação

Outras Informações

ID Authenticus: P-00M-3MK

DOI: 10.3233/978-1-61499-668-2-483

Abstract (EN): Sales forecasts gained more importance in the retail industry with the increasing of promotional activity, not only because of the considerable portion of products under promotion but also due to the existence of promotional activities, which boost product sales and make forecasts more difficult to obtain. This study is performed with real data from a Portuguese consumer goods retail company, from January 2012 until April 2015. To achieve the purpose of the study, dynamic regression is used based on information of the focal product and its competitors, with seasonality modelled using Fourier terms. The selection of variables to be included in the model is done based on the lowest value of AIC in the train period. The forecasts are obtained for a test period of 30 weeks. The forecasting models overall performance is analyzed for the full period and for the periods with and without promotions. The results show that our proposed dynamic regression models with price and promotional information of the focal product generate substantially more accurate forecasts than pure time series models for all periods studied.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6