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Measure of bullwhip effect in supply chains with first-order bivariate vector autoregression time-series demand model
اندازه گیری اثرات شلاق چرمی در زنجیره های تامین با مدل تقاضای سری زمانی اتورگرسیون بردار دوبعدی سطح اول-2017 With supply chains becoming increasingly global, the issue of bullwhip effect, a phenomenon attribu
table to demand fluctuation in the upstream section of the supply chains, has received greater attention
from many researchers. However, most existing research studies on quantifying the bullwhip effect were
conducted under the first-order autoregressive [AR(1)] incoming demand process or its variants as the
fundamental demand process, thereby failing to account for the retailer demand dependency. This re
search work thus examined the bullwhip effect for the first-order bivariate vector autoregression [VAR
(1)] demand process in a two-stage supply chain consisting of one supplier and two retailers. The im
pacts of the correlation parameters of the demand process, the correlation coefficient between the two
error terms, and the variances of the error terms on the bullwhip effect were investigated. As such, the
measure of the bullwhip effect was established using an analytical approach in which the minimum
mean square error (MMSE) forecasting method and the base stock policy were applied to all members of
the supply chain. Numerical experiments were then conducted to illustrate the behavior of the bullwhip
effect with respect to various parameters of the demand processes to see in which situations the bull
whip effect would be absent. In addition, an evaluation of the inventory variance ratio was analyzed.
Keywords: Supply chain | Bullwhip effect | Bivariate VAR(1) model | Base stock policy |
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