Original scientific paper

https://doi.org/10.5552/drind.2018.1770

Performance Comparison between ARIMAX, ANN and ARIMAX-ANN Hybridization in Sales Forecasting for Furniture Industry

Melih Yucesan orcid.org/0000-0001-6148-4959 ; Munzur University, Engineering Faculty, Department of Mechanical Engineering, Tunceli, Turkey
Muhammet Gul orcid.org/0000-0002-5319-4289 ; Munzur University, Engineering Faculty, Department of Industrial Engineering, Tunceli, Turkey
Erkan Celik orcid.org/0000-0003-4465-0913 ; Munzur University, Engineering Faculty, Department of Industrial Engineering, Tunceli, Turkey

Abstract

Manufacturing firms aim to increase their profits and reduce costs in a competitive and rapidly changing market. One of the most important ways to reach these goals is to forecast sales correctly. Furniture manufacturing, which is considered a prosperous and growing industry in Turkey, has an increasing trend related to the growth in construction and associated industries, increase in urban migration and increase in per capita income. Accuracy of sales forecasting in furniture industry is affected by external factors, such as consumer confidence index, producer price index, month of the year and number of vacation days as well as the time factor itself. This study aims to develop an Autoregressive Integrated Moving Average with external variables (ARIMAX) to forecast the total monthly sales of furniture products of a well-known manufacturer in Turkey. As a follow up study, a performance comparison between ARIMAX, artificial neural networks (ANNs) and ARIMAX-ANN hybridization is performed. In conclusion, results of performance measures demonstrate that hybrid model developed for each amount of product sales give better accuracy values than single methods. Overall, it is proved that using the ARIMAX and hybridization of this method with ANN are applicable for forecasting monthly sales of furniture products.

Keywords

ARIMAX; ANN; hybrid method; sales forecasting; furniture industry

Hrčak ID:

214107

URI

https://hrcak.srce.hr/214107

Publication date:

28.12.2018.

Article data in other languages: croatian

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