Artificial neural networks in marketing

Silva, M.M. and Moutinho, L. (2015) Artificial neural networks in marketing. In: Lee, N. and Farrell, A. M. (eds.) Wiley Encyclopaedia of Management: Volume 9 Marketing. Wiley. (doi: 10.1002/9781118785317.weom090180)

Abstract

This article is designed to give the reader the key insights into the world of artificial neural networks (ANNs), seen here as generalized mathematical models that emulate human cognition. The inner workings of ANNs are highlighted such as the topology itself, activation function, connection weights, combination function, distribution of outputs, sigmoid function, network architecture, its multilayer nature, high-order statistics, feedforward networks, learning process, training patterns, the perceptron model, backpropagation (BP) algorithm, among many other technical issues. The entry also includes many multiple academic research applications in marketing. The entry concludes with an overview of key developments in this area like Hopfield neural networks.

• Item Type: Book Sections
• Status: Published
• Glasgow Author(s) Enlighten ID: Moutinho, Professor Luiz
• Authors: Silva, M.M., and Moutinho, L.
• College/School: College of Social Sciences > Adam Smith Business School > Management
• Publisher: Wiley