Explaining the underlying psychological factors of consumer behaviour with artificial neural networks

Greene, Max 2016. Explaining the underlying psychological factors of consumer behaviour with artificial neural networks. PhD Thesis, Cardiff University. Item availability restricted.

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Abstract

This thesis intends to advance our understanding of consumer behaviour, and proposes an extension to the theoretical and methodological framework of the Behavioural Perspective Model. Drawing on the intellectual tradition of connectionism and employing advanced artificial neural network modelling techniques, the research programme described here assesses the appropriateness of connectionist architectures in explaining consumer behaviour. This thesis traces the developments in the fields of consumer behaviour analysis to critically evaluate the significance of limitations inherited from radical behaviourism, and proposes a hybrid connectionist approach to address these methodological constraints. The study is both highly quantitative and interpretative in nature, and generates a large body of empirical evidence to support the methodological and theoretical deliberations. Two types of data are used here: a simulated dataset to assess the capacity of the pruning algorithms to reveal the underlying relations within the data; and a consumer panel dataset to which the neural network algorithms are applied to develop predictive, descriptive, and interpretative connectionist models that aim to explain the consumer purchasing decision-making process. Even though it is beyond the scope of this research project to propose mechanisms to explain all elements of consumer purchasing decision and it will therefore remain to be addressed as part of an ongoing collaborative research programme, the main conclusion to be drawn from this work is that the connectionist framework and artificial neural networks can be considered a significant contribution to the extension of theoretical and philosophical framework of intentional behaviourism.

Item Type:	Thesis (PhD)
Date Type:	Completion
Status:	Unpublished
Schools:	Business (Including Economics)
Subjects:	H Social Sciences > HF Commerce
Date of First Compliant Deposit:	22 September 2016
Last Modified:	22 Dec 2021 11:55
URI:	https://orca.cardiff.ac.uk/id/eprint/94702

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