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Export sales forecasting using artificial intelligence

Author

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  • Sohrabpour, Vahid
  • Oghazi, Pejvak
  • Toorajipour, Reza
  • Nazarpour, Ali

Abstract

Sales forecasting is important in production and supply chain management. It affects firms’ planning, strategy, marketing, logistics, warehousing and resource management. While traditional time series forecasting methods prevail in research and practice, they have several limitations. Causal forecasting methods are capable of predicting future sales behavior based on relationships between variables and not just past behavior and trends. This research proposes a framework for modeling and forecasting export sales using Genetic Programming, which is an artificial intelligence technique derived from the model of biological evolution. Analyzing an empirical case of an export company, an export sales forecasting model is suggested. Moreover, a sales forecast for a period of six weeks is conducted, the output of which is compared with the real sales data. Finally, a variable sensitivity analysis is presented for the causal forecasting model.

Suggested Citation

  • Sohrabpour, Vahid & Oghazi, Pejvak & Toorajipour, Reza & Nazarpour, Ali, 2021. "Export sales forecasting using artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    • Handle: RePEc:eee:tefoso:v:163:y:2021:i:c:s0040162520313068
    DOI: 10.1016/j.techfore.2020.120480
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    8. Che-Yu Hung & Chien-Chih Wang & Shi-Woei Lin & Bernard C. Jiang, 2022. "An Empirical Comparison of the Sales Forecasting Performance for Plastic Tray Manufacturing Using Missing Data," Sustainability, MDPI, vol. 14(4), pages 1-21, February.
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