Nazarpour, Ali (2021) Export sales forecasting using artificial intelligence. Technological Forecasting and Social Change, 163 (120480). ISSN 0040-1625

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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.

Item Type:	Article
Additional Information:	© 2020 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/. Cite as: Vahid Sohrabpour, Pejvak Oghazi, Reza Toorajipour, Ali Nazarpour, Export sales forecasting using artificial intelligence, Technological Forecasting and Social Change, Volume 163, 2021, 120480, ISSN 0040-1625, https://doi.org/10.1016/j.techfore.2020.120480. (https://www.sciencedirect.com/science/article/pii/S0040162520313068)
Keywords:	Artificial intelligence; Causal forecasting; Export sales forecast; Genetic programming; Modeling;
Academic Unit:	Faculty of Social Sciences > School of Business
Item ID:	14706
Identification Number:	https://doi.org/10.1016/j.techfore.2020.120480
Depositing User:	Ali Nazarpour
Date Deposited:	18 Aug 2021 14:13
Journal or Publication Title:	Technological Forecasting and Social Change
Publisher:	Elsevier
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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