Abstract
A review of the literature indicates that few studies have used artificial neural networks (ANNs) for data analysis in business and marketing research, even though there are many benefits to the use of ANNs. Therefore, this article discusses neural networks (NNs) that can be used in addition to or as an alternative to linear regression for data analysis in strategic marketing. The function and layout of NNs make them ideal for research dealing with nonlinear, incomplete, unspecified, or ‘fuzzy’ data and offer several advantages over linear regression. Unfortunately, in many marketing studies, the information being modeled is far from flawless and is often riddled with ambiguities linear regression is insufficient to accurately assess. NNs could be employed for great benefit by researchers analyzing the nonlinear, complex relationships in business data. The article discusses examples of types of studies that could be strengthened or expanded from neural network use.
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