This paper compares two vastly different methods of analysis-multiple regression and neural networks, in supply chain flexibility assessment. Data of manufacturing firms evaluating their prominent suppliers were analysed by multiple regression and simulated using three-layer multilayer perceptron (MLP) neural networks. Our study shows that NN can accurately determine a supplier's flexibility capability within an error of 1% The incorporation of these two methods can lead to better understanding and dynamic prediction of supply chain flexibility for buyers. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Jeeva, A. S., & Guo, W. W. (2010). Supply chain flexibility assessment by multivariate regression and neural networks. In Lecture Notes in Electrical Engineering (Vol. 67 LNEE, pp. 845–852). https://doi.org/10.1007/978-3-642-12990-2_98
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