Abstract
This paper introduces a debate about some potentialities of Neural Network (NN) technology in supporting ’modelling and solving’ activities for ’complex’ multicriteria decision problems. The paper is application oriented in the field of Marketing and Product Planning (MPP). In particular, it discusses an NN-model developed to support the MPP management of a factory in conceiving some strategic decisions about prices and product performance levels in an oligopolistic market.
The new approach has shown very interesting properties, under a perspective which conceives a NN as a tool for building explicative models in relation with a complex system that cannot be (satisfactorily) represented by formal models or solved by traditional tools. The approach has contributed successfully in defining an explicative model of market behaviour. This representation can be used to deduce answers to a few ’how’ questions about one product possibility of ’eroding’ market shares from competitors.
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© 1994 Springer Science+Business Media New York
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Gianoglio, P., Ostanello, A. (1994). Multiple Choices in an Oligopolistic Market: Explicative Models and Neural Networks. In: Ríos, S. (eds) Decision Theory and Decision Analysis: Trends and Challenges. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-1372-4_19
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DOI: https://doi.org/10.1007/978-94-011-1372-4_19
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-4600-8
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