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American Journal of Business and Operations Research
Volume 10 , Issue 2, PP: 39-51 , 2023 | Cite this article as | XML | Html |PDF

Title

A Comparative Analysis of Traditional Forecasting Methods and Machine Learning Techniques for Sales Prediction in E-commerce

  Irina V. Pustokhina 1 * ,   Denis A. Pustokhin 2

1  Department of Entrepreneurship and Logistics, Plekhanov Russian University of Economics, Moscow 117997, Russia
    (Pustohina.IV@rea.ru)

2  Department of Logistics, State University of Management , Moscow 109542,
    (da_pustohin@guu.ru)

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Doi   :   https://doi.org/10.54216/AJBOR.100205

Received: December 05, 2022 Revised: February 05, 2023 Accepted: March 20, 2023

Abstract :

This paper presents a comparative analysis of traditional forecasting methods and machine learning (ML) techniques for sales prediction in e-commerce.  We first review the literature on both traditional and ML methods for sales prediction in e-commerce, highlighting their strengths and weaknesses. The study uses a dataset of daily sales from an e-commerce retailer to conduct a comprehensive empirical study thar compares the performance of literature methods from both categories. The analysis considers different forecasting horizons and evaluates the accuracy of the predictions using various performance metrics, such as mean absolute error and mean squared error. The study finds that ML techniques generally outperform traditional methods, especially for longer forecasting horizons. However, some traditional methods, such as the Holt-Winters method, can also perform well under certain conditions. Our study provides insights into the relative strengths and weaknesses of traditional and ML methods for sales prediction in e-commerce and can guide practitioners in selecting appropriate methods for their specific requirements.

Keywords :

Forecasting; Sales Prediction; E-Commerce; machine Learning

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Cite this Article as :
Style #
MLA Irina V. Pustokhina, Denis A. Pustokhin. "A Comparative Analysis of Traditional Forecasting Methods and Machine Learning Techniques for Sales Prediction in E-commerce." American Journal of Business and Operations Research, Vol. 10, No. 2, 2023 ,PP. 39-51 (Doi   :  https://doi.org/10.54216/AJBOR.100205)
APA Irina V. Pustokhina, Denis A. Pustokhin. (2023). A Comparative Analysis of Traditional Forecasting Methods and Machine Learning Techniques for Sales Prediction in E-commerce. Journal of American Journal of Business and Operations Research, 10 ( 2 ), 39-51 (Doi   :  https://doi.org/10.54216/AJBOR.100205)
Chicago Irina V. Pustokhina, Denis A. Pustokhin. "A Comparative Analysis of Traditional Forecasting Methods and Machine Learning Techniques for Sales Prediction in E-commerce." Journal of American Journal of Business and Operations Research, 10 no. 2 (2023): 39-51 (Doi   :  https://doi.org/10.54216/AJBOR.100205)
Harvard Irina V. Pustokhina, Denis A. Pustokhin. (2023). A Comparative Analysis of Traditional Forecasting Methods and Machine Learning Techniques for Sales Prediction in E-commerce. Journal of American Journal of Business and Operations Research, 10 ( 2 ), 39-51 (Doi   :  https://doi.org/10.54216/AJBOR.100205)
Vancouver Irina V. Pustokhina, Denis A. Pustokhin. A Comparative Analysis of Traditional Forecasting Methods and Machine Learning Techniques for Sales Prediction in E-commerce. Journal of American Journal of Business and Operations Research, (2023); 10 ( 2 ): 39-51 (Doi   :  https://doi.org/10.54216/AJBOR.100205)
IEEE Irina V. Pustokhina, Denis A. Pustokhin, A Comparative Analysis of Traditional Forecasting Methods and Machine Learning Techniques for Sales Prediction in E-commerce, Journal of American Journal of Business and Operations Research, Vol. 10 , No. 2 , (2023) : 39-51 (Doi   :  https://doi.org/10.54216/AJBOR.100205)
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