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Paper proposal. Theme: The customer demand forecasting for E-SCM applications. Zhang Shuzhu. Background:. E-SCM Forecasting Bullwhip effect. Previous knowledge:. Longer lead times and poor selection of forecasting model parameters lead to strong bullwhip effect in E-SCM;

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slide1

Paper proposal

Theme:

The customer demand forecasting for E-SCM applications

Zhang Shuzhu

slide2

Background:

  • E-SCM
  • Forecasting
  • Bullwhip effect
slide3

Previous knowledge:

  • Longer lead times and poor selection of forecasting model parameters lead to strong bullwhip effect in E-SCM;
  • Increased seasonality helps to reduce the bullwhip effect.
assumptions
Assumptions:
  • A two-stage E-supply chain that consists of one supplier and one on-line retailer.
  • The supplier provides a single product for the on-line retailer, while the on-line retailer fulfills the requirements of the on-line customers at the marketplace through the distribution center.
assumptions1
Assumptions:

1.The actual customer demand emerges at the marketplace, and the retailer fulfills the customer demand by on-hand inventory, and any unfulfilled customer demands are backordered.

here we suppose that retailer use (s, S) policy .

s=LT*AVG + z*STD* √LT

Q= √(2*K*AVG)/h

S=Q + s

2. We assume that the supplier delivers all orders of the on-line retailer after a fixed lead time (L) so that it will simplify the retailer’s replenishment policy.

slide6

Basic simulated supply chain model

We’ll try to find which kinds of parameters, methods, or factors can be used to keep the bullwhip ration low, while at the same time to increase forecast accuracy.