Production
https://prod.org.br/article/doi/10.1590/0103-6513.20220006
Production
Research Article

Multi-criteria approach to adjust demand forecast for products: application of analytic hierarchy process

Lidiane Cristina de Oliveira; Bruna Cristine Scarduelli Pacheco; Claudio Luis Piratelli

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Abstract

Paper aims: Investigate whether the results of time series models can be adjusted with the AHP method towards a more assertive forecast.

Originality: Considering demand forecasting as a complex decision-making situation, this research investigated the use of the AHP as a complement to traditional forecasting methods.

Research method: This applied research employed, as main procedures, literature review and mathematical modeling.

Main findings: Two models were proposed that presented satisfactory results: model I reduced the forecast error by 16% in January, 25% in February, 37% in March, 3% in April, and 7% in May; model II reduced it by 17% in January, 21% in February, 29% in March, 2% in April, and 5% in May.

Implications for theory and practice: We conclude that the AHP has the potential to correct the results of time series in the textile industry by allowing the incorporation of quantitative and qualitative variables.

Keywords

Demand forecasting, Analytic hierarchy process, Textile industry

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Submitted date:
01/24/2022

Accepted date:
07/12/2022

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