Consumer perceptions of ATMs: an application of neural networks

This paper reports on the results of research aimed at using Neural Network methods to model consumer attitudes towards Automated Teller Machines (ATMs). The approach is based on an analogy of the workings of the human brain, using a set of interconnected neurons. It involves quantifying the interconnections by means of a statistically based learning procedure. The model was tested on data derived from a consumer survey, and the results obtained were encouraging.

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