Determining supply chain flexibility using statistics and neural networks: a comparative study
The purpose of this paper is to examine the application of neural networks as a flexibility andperformance measure in supplier-manufacturer activities. The dimensions of information exchange,supplier integration, product delivery, logistics, and organisational structure are used as determinantsfacto...
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| Format: | Conference Paper |
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Conference Publishing Services
2009
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| Online Access: | http://hdl.handle.net/20.500.11937/9696 |
| Summary: | The purpose of this paper is to examine the application of neural networks as a flexibility andperformance measure in supplier-manufacturer activities. The dimensions of information exchange,supplier integration, product delivery, logistics, and organisational structure are used as determinantsfactors affecting this supply chain flexibility. The data set was collected from more than 200 Australianmanufacturing firms evaluating their suppliers. Our study shows that neural networks can accuratelydetermine a supplier's flexibility with an error within 1%, which is more accurate than the conventional multivariate regression can. |
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