Modelling near-real-time order arrival demand in e-commerce context: a machine learning predictive methodology

Volume: 120, Issue: 6, Pages: 1149 - 1174
Published: May 5, 2020
Abstract
Purpose Accurate prediction of order demand across omni-channel supply chains improves the management's decision-making ability at strategic, tactical and operational levels. The paper aims to develop a predictive methodology for forecasting near-real-time e-commerce order arrivals in distribution centres, allowing third-party logistics service providers to manage the hour-to-hour fast-changing arrival rates of e-commerce orders better....
Paper Details
Title
Modelling near-real-time order arrival demand in e-commerce context: a machine learning predictive methodology
Published Date
May 5, 2020
Volume
120
Issue
6
Pages
1149 - 1174
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