Export sales forecasting using artificial intelligence

Vahid Sohrabpour, Pejvak Oghazi, Reza Toorajipour and Ali Nazarpour

Technological Forecasting and Social Change, 2021, vol. 163, issue C

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.

Keywords: Causal forecasting; Modeling; Export sales forecast; Genetic programming; Artificial intelligence (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:163:y:2021:i:c:s0040162520313068

DOI: 10.1016/j.techfore.2020.120480

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