Enhancing Demand Forecasting in Retail Supply Chains: A Machine Learning Regression Approach

Authors

  • Tewogbade Shakir

  • Akinlose Modupe

Abstract

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How to Cite

Enhancing Demand Forecasting in Retail Supply Chains: A Machine Learning Regression Approach. (2023). Global Journal of Management and Business Research, 23(A8), 1-15. https://journalofbusiness.org/index.php/GJMBR/article/view/102919

 

References

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Real Carbonneau, Kevin Laframboise, Rustam Vahidov (2008) Application of machine learning techniques for supply chain demand forecasting. 184(3), 1140-1154.

M Casson (2013) Economic analysis of international supply chains: An internalization perspective. 49(2), 8-13.

Rohit Sanjay Pitale, Paras Arora, Charumani Singh, Darpan Malkan (2011) EVOLUTION OF UNITIZATION IN E-COMMERCE SUPPLY CHAIN. 111-122.

David Ketchen, Larry Giunipero (2004) The intersection of strategic management and supply chain management. 33(1), 51-56.

J Hope, R Fraser (2003) Beyond budgeting: how managers can break free from the annual performance trap. 41(05), 41-2908-41-2908.

G Wang (2012) Unknown Title. 29, 280-284.

(null) Video for A Novel Dynamic Demand Forecasting Model for Resilient Supply Chains using Machine Learning.

Enhancing Demand Forecasting in Retail Supply Chains: A Machine Learning Regression Approach

Published

2023-10-16

Issue

Vol. 23 No. A8 (2023): GJMBR-A Administration & Management: Volume 23 Issue A8

Section

Articles

License

Copyright (c) 2023 Authors and Global Journals Private Limited

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Enhancing Demand Forecasting in Retail Supply Chains: A Machine Learning Regression Approach. (2023). Global Journal of Management and Business Research, 23(A8), 1-15. https://journalofbusiness.org/index.php/GJMBR/article/view/102919