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Modelling Satisfaction with Automated Banking Channels

Beynon, Malcolm James, Goode, Mark M. H., Moutinho, Luiz A. and Snee, Helena R. 2005. Modelling Satisfaction with Automated Banking Channels. Services Marketing Quarterly 26 (4) , pp. 77-94. 10.1300/J396v26n04_05

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Abstract

The aim of this paper is to apply a new technique, i.e., Variable Precision Rough Set Theory (VPRS) to explaining consumer satisfaction with automated banking channels. VPRS is a new development on the original Rough Set Theory (RST) (for a discussion of RST see Slowinski et al. (1997) or Dimitras et al. (1999), for a discussion of VPRS see Ziarko, 1993a or 1993b), that not only estimates deterministic rules like RST (If … then …) but also probabilistic rules as well. The major advantage of these rules is that marketing managers can easily understand them, and this allows these managers to focus limited resources on meeting or exceeding the needs of particular consumers. A fairly simple model is used in this paper to illustrate the use of VPRS, which links overall satisfaction from ATM's to nine exogenous variables.This paper is divided into five parts, the first of which is a brief introduction to the technique of Rough Set Theory. The second describes developments in RST, VPRS and the literature on customer satisfaction. The third section describes the methodology and data collection. The fourth section analyses the empirical results derived from applying the VPRS model. Finally the last section discusses the results and managerial implications of the results obtained from this study and its implications for marketing management. To date VPRS has only been applied to a very small number of business research environments (see Beynon et al. (2001) or Beynon and Peel (2002)).

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HG Finance
Q Science > QA Mathematics
Uncontrolled Keywords: ATMs, banking channels, Variable Precision Rough Set Theory, rule generation, overall satisfaction, marketing management
Publisher: Taylor & Francis
ISSN: 1533-2969
Last Modified: 04 Jun 2017 04:23
URI: http://orca.cf.ac.uk/id/eprint/38000

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