Export Sales Forecasting Using Artificial Intelligence

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

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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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.
Original languageEnglish
Article number120480
JournalTechnological Forecasting and Social Change
Volume163
Number of pages10
ISSN0040-1625
DOIs
Publication statusPublished - Feb 2021

Bibliographical note

Published online: 24 November 2020.

Keywords

  • Causal forecasting
  • Modeling
  • Export sales forecast
  • Genetic programming
  • Artificial intelligence

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