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Exploring a Downstream Demand Inference Strategy in a Decentralized Two-Level Supply Chain
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Author(s): Youssef Tliche (University of Le Havre Normandie, France), Atour Taghipour (Normandy University, France) and Béatrice Canel-Depitre (University of Le Havre Normandie, France)
Copyright: 2021
Pages: 65
Source title:
Demand Forecasting and Order Planning in Supply Chains and Humanitarian Logistics
Source Author(s)/Editor(s): Atour Taghipour (Normandy University, France)
DOI: 10.4018/978-1-7998-3805-0.ch001
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Abstract
A coordination approach for forecast operations, known as downstream demand inference, enables an upstream actor to infer the demand information at his formal downstream actor without the need for information sharing. This approach was validated if the downstream actor uses the simple moving average (SMA) forecasting method. To answer an investigative question through other forecasting methods, the authors use the weighted moving average (WMA) method, whose weights are determined in this work thanks to the Newton's optimization of the upstream average inventory level. Starting from a two-level supply chain, the simulation results confirm the ability of the approach to reduce the mean squared error and the average inventory level, compared to a decentralized approach. However, the bullwhip effect is only improved after a certain threshold of the parameter of the forecasting method. Still within the framework of the investigation, they carry out a comparison study between the adoption of the SMA method and the WMA method. Finally, they generalize their results for a multi-level supply chain.
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