Abstract
This article addresses the application of neural networks to the problem of predicting store performance. The article considers the predictive power of neural networks, but concentrates on the issues associated with using them, in particular, whether neural networks can be successfully applied by managers with a rudimentary knowledge of personal computing.
Additional information
Notes on contributors
David Coates
DAVE COATES (left) is a lecturer in statistics at Loughborough University Business School. His main research interests include applied statistics, time series analysis and total quality management. He has previously worked as a systems analyst for T I Chesterfield plc, and as a senior lecturer in statistics at the University of Plymouth.
Neil Doherty
NEIL DOHERTY (right) is a lecturer in management information systems at Loughborough University Business School. He has 10 years experience in the oil and aerospace industries. His research interests include the management applications of intelligent knowledge based systems, organisational issues in systems development and success factors in systems development.
Alan French
ALAN FRENCH (left) is a lecturer in quantitative methods at Loughborough University Business School. Previously he worked for the Central Electricity Generating Board as a systems programmer. Research interests include management applications of neural networks, genetic algorithms and integer programming.
Malcolm Kirkup
MALCOLM KIRKUP (right) is a lecturer in retailing at Loughborough University Business School. Formerly marketing planning manager with Sears plc, and lecturer in marketing at Cranfield University and Aston Business School. His research interests include retail location assessment and the application of computer models in retail location analysis.