Supply chain flexibility assessment by multivariate regression and neural networks
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(...
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| Format: | Book Chapter |
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Springer-Verlag
2010
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| Online Access: | http://hdl.handle.net/20.500.11937/45545 |
| Summary: | 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. |
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