Forecasting Monthly Sales of White Goods Using Hybrid Arimax and Ann Models
In
this study, hybrid ARIMAX-ANN and SARIMAX-ANN sales forecasting models are proposed
for a white goods wholesaler. White goods industry which is one of the durable
goods sub-sector includes washing machines, dishwashers, refrigerators and
small home appliances. In making forecasts, 46-month sales data of a white
goods wholesaler are used. Factors influencing sales such as exchange rate,
holidays, consumer confidence index (CCI), producer price index (PPI) and
residential sales of the region are used as explanatory variables. The study
contributes to the current literature by some aspects. First, there is no
attempts applying the ARIMAX-ANN and SARIMAX-ANN hybrid models to forecast
sales data in white goods industry. Second, the hybrid models combine the
advantages of times series and ANN models. ARIMAX models are insufficient to solve
complex nonlinear problems. On the other hand, ANN is sufficient to explain
nonlinear relationships. On conclusion, use of hybrid models can increase the
accuracy of the models.
Forecasting Monthly Sales of White Goods Using Hybrid Arimax and Ann Models
In this study, hybrid ARIMAX-ANN and SARIMAX-ANN sales
forecasting models are proposed for a white goods wholesaler. White goods industry
which is one of the durable goods sub-sector includes washing machines,
dishwashers, refrigerators and small home appliances. In making forecasts, 46-month
sales data of a white goods wholesaler are used. Factors influencing sales such
as exchange rate, holidays, consumer confidence index (CCI), producer price
index (PPI) and residential sales of the region are used as explanatory
variables. The study contributes to the current literature by some aspects.
First, there is no attempts applying the ARIMAX-ANN and SARIMAX-ANN hybrid
models to forecast sales data in white goods industry. Second, the hybrid
models combine the advantages of times series and ANN models. ARIMAX models are
insufficient to solve complex nonlinear problems. On the other hand, ANN is
sufficient to explain nonlinear relationships. On conclusion, use of hybrid
models can increase the accuracy of the models.
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