Towards connectionist models of food consumer attitudes

This paper is in keeping with a long term research program in the field of marketing and particularly in the study of consumer behaviour. In continuation with the cognitivist paradigm, a connectionist approach to attitude modelling is proposed and the theoretical and metatheoretical bases of this research are presented. This orientation consists of studying how the recourse to the neural networks should be constituting an interesting and innovative decision support in this field. This research is particularly based on Beckwith and Lehmann's (1975) model which is inspired by Fishbein's (1963) linear and additive representation of the attitude concept and Bass and Talarzyk's (1972) model. It is demonstrated how a basic automata network can improve knowledge of attitude dynamics by showing different attractors (fixed points and limit cycles). This work opens a new research axis in the food marketing area.