ATM user attitudes: a neural network analysis

Fiona Davies (Cardiff Business School, University of Wales, Cardiff)
Luiz Moutinho (Cardiff Business School, University of Wales, Cardiff)
Bruce Curry (Cardiff Business School, University of Wales, Cardiff)

Marketing Intelligence & Planning

ISSN: 0263-4503

Publication date: 1 April 1996

Abstract

Shows how neural networks can bring together psychometric and econometric approaches to the measurement of attitudes and perceptions. Uses a neural network to analyse data collected from a sample of ATM users on their perceptions of ATM service. Uses the weights of connections from input nodes to hidden nodes to label the hidden nodes to represent particular respondent attitudes. Uses the network to analyse the impact of explanatory (input layer) variables on the hidden layer attributes, and through these on the endogenous (output layer) variables ‐ satisfaction with ATMs, likelihood of recommendation to others, extent and frequency of use. Defines four user types, characterized as “disaffected youth”, “technophobes”, the “pro‐technology” segment, and the “cost conscious” segment. Gives some ideas on how banks could address the needs of each segment.

Keywords

Citation

Davies, F., Moutinho, L. and Curry, B. (1996), "ATM user attitudes: a neural network analysis", Marketing Intelligence & Planning, Vol. 14 No. 2, pp. 26-32. https://doi.org/10.1108/02634509610110778

Download as .RIS

Publisher

:

MCB UP Ltd

Copyright © 1996, MCB UP Limited

Please note you might not have access to this content

You may be able to access this content by login via Shibboleth, Open Athens or with your Emerald account.
If you would like to contact us about accessing this content, click the button and fill out the form.
To rent this content from Deepdyve, please click the button.