An Intelligent Approach for Demand Forecasting in E-commerce

Samah I. Abdel

doi:https://doi.org/10.54216/AJBOR.010203

Full Length Article

Volume 1 • Issue 2 • PP: 77-83 • 2020

An Intelligent Approach for Demand Forecasting in E-commerce

Samah I. Abdel Aal ^1*

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¹Department of Information Systems, Faculty of Computers and Informatics, Zagazig University, Sharkia, Zagazig, 44519, Egypt

* Corresponding Author.

DOI https://doi.org/10.54216/AJBOR.010203

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Received: May 16, 2020 Accepted September 17, 2020

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Abstract

With the growth of e-commerce, accurate demand forecasting has become a critical aspect of successful business operations. Traditional demand forecasting techniques such as time-series analysis, moving averages, and exponential smoothing have been used for years, but they have limitations in capturing the complex and dynamic nature of e-commerce demand. In this paper, we explore innovative approaches to demand forecasting in e-commerce. Specifically, we discuss the use of tree-based Machine Learning (ML) techniques as well as advanced statistical models such as Bayesian networks and hierarchical models. We provide a case study of successful implementations of innovative demand forecasting techniques in e-commerce companies. The results show that our approach can significantly improve inventory management and logistics strategies, leading to increased profitability and customer satisfaction.

Keywords

Machine Learning (ML) Forcasting Intelligent Systems E-Commerce

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Aal, Samah I. Abdel. "An Intelligent Approach for Demand Forecasting in E-commerce." American Journal of Business and Operations Research, vol. Volume 1, no. Issue 2, 2020, pp. 77-83. DOI: https://doi.org/10.54216/AJBOR.010203

Aal, S. (2020). An Intelligent Approach for Demand Forecasting in E-commerce. American Journal of Business and Operations Research, Volume 1(Issue 2), 77-83. DOI: https://doi.org/10.54216/AJBOR.010203

Aal, Samah I. Abdel. "An Intelligent Approach for Demand Forecasting in E-commerce." American Journal of Business and Operations Research Volume 1, no. Issue 2 (2020): 77-83. DOI: https://doi.org/10.54216/AJBOR.010203

Aal, S. (2020) 'An Intelligent Approach for Demand Forecasting in E-commerce', American Journal of Business and Operations Research, Volume 1(Issue 2), pp. 77-83. DOI: https://doi.org/10.54216/AJBOR.010203

Aal S. An Intelligent Approach for Demand Forecasting in E-commerce. American Journal of Business and Operations Research. 2020;Volume 1(Issue 2):77-83. DOI: https://doi.org/10.54216/AJBOR.010203

S. Aal, "An Intelligent Approach for Demand Forecasting in E-commerce," American Journal of Business and Operations Research, vol. Volume 1, no. Issue 2, pp. 77-83, 2020. DOI: https://doi.org/10.54216/AJBOR.010203

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