Forecasting Preliminary Order Cost to Increase Order Management Performance: A Case Study in the Apparel Industry

Tüzin Akçinar Günsari, Aysegül Kaya and Yeliz Ekinci
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Tüzin Akçinar Günsari: TYH Textile, Turkey
Aysegül Kaya: TYH Textile, Turkey
Yeliz Ekinci: İstanbul Bilgi University, Turkey

International Journal of Business Analytics (IJBAN), 2022, vol. 9, issue 5, 1-15

Abstract: In this study, the cost estimation to be used in the optimization of proposed order price offer is made by artificial neural network (ANN) method. A case study is performed by the real data of a company, and the forecast results of the traditional arithmetic model used by the company and the proposed ANN based method are compared and it is seen that the proposed method results outperform the other. The biggest contribution of this study to companies is to increase the company’s order management performance by helping the company to make more accurate pricing due to more accurate cost estimation. Moreover, to the best of our knowledge, this is the first study on forecasting preliminary order cost in the apparel industry and fills an important gap in the literature.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jban00:v:9:y:2022:i:5:p:1-15

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