Evaluating the Value of Information Sharing in a Supply Chain

4430 Words Nov 10th, 2012 18 Pages
Int J Adv Manuf Technol (2006) 27: 604–609 DOI 10.1007/s00170-004-2214-4


J.M. Hsiao · C.J. Shieh

Evaluating the value of information sharing in a supply chain using an ARIMA model

Received: 10 October 2003 / Accepted: 20 April 2004 / Published online: 9 February 2005 © Springer-Verlag London Limited 2005 Abstract This paper considers a two-echelon supply chain, which contains one supplier and one retailer. It studies the quantification of the bullwhip effect and the value of informationsharing between the supplier and the retailer under an autoregressive integrated moving average (ARIMA) demand of (0, 1, q). The results show that with an increasing value of q, bullwhip effects will be more obvious, no matter
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Under the mode of auto regression (AR(1)) to predict the demand, Chen [4] theoretically confirms the existence of bullwhip effect and provides a quantitative analysis of the variability for each level in a supply chain. In this study, we use an autoregressive integrated moving average (ARIMA) model to study the value of information sharing. ARIMA can be more complex to use than statistical forecasting techniques, but if it is implemented properly, it can be quite powerful and flexible. ARIMA was first developed in the late 1960s but was systemized by Box and Jenkins in 1976 [2]. ARIMA is widely used in modeling and forecasting time series. There were two factors that must be determined in order to use the ARIMA model. One is the length of weights, how much of the past information should be used to forecast the next observation. The other is the value of the weight. The order of an ARIMA model is usually denoted by ( p,d,q) [7], where p is the order of the autoregressive part AR( p), d is the order of differencing, and q is the order the moving-average process MA(q). General speaking, p denotes mean pulses, d denotes mean level shifts and q denotes mean local time trends. Since ARIMA is widely applied and possesses various good qualities, this study, based on a two-echelon supply chain, i.e.,

1 Introduction

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