Information distortion in a supply chain: the bullwhip effect
Management Science - Special issue on frontier research in manufacturing and logistics
Evolving artificial neural networks to combine financial forecasts
IEEE Transactions on Evolutionary Computation
Combination of artificial neural-network forecasters for prediction of natural gas consumption
IEEE Transactions on Neural Networks
Service chain-based business alliance formation in service-oriented architecture
Expert Systems with Applications: An International Journal
The agile improvement of MMORPGs based on the enhanced chaotic neural network
Knowledge-Based Systems
Fashion retailing forecasting based on extreme learning machine with adaptive metrics of inputs
Knowledge-Based Systems
A seasonal discrete grey forecasting model for fashion retailing
Knowledge-Based Systems
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In order to honour customer demand and sustain quality of service in BT's service chain, accurate forecasting for customer demand is critical for optimal resource planning. In the more general context of service organisations, failure to allocate sufficient resources to meet anticipated customer demand will lead to delayed or disrupted service provision which in turn will result in degraded quality of service for customers and ill-balanced utilisation of available resources. In this paper, we present our ongoing research on a prototype collaborative forecasting application, whereas organisations involved in a supply and demand partnership aim to co-operate by sharing and jointly forming forecasts to aid in resource planning. We identify key theoretical and implementation specific issues related to the area of collaborative forecasting and discuss our initial modular artificial neural network approach to the problem.