Abstract
New product development decisions are among the most important decisions that usually draw the attention and concern of top level managers in most modern companies. Prior to the introduction of the new product, market simulations can be used as a very useful and inexpensive tool for laboratory experiments. These simulations can lead the decision maker to the selection of the most promising penetration strategy for the product under development and thus reducing the relevant risk. In this paper, inductive learning algorithms are used in order to perform various market simulations and gain some knowledge, in the form of rules, concerning the behaviour and preferences of the consumers.
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Matsatsinis, N.F., Samaras, A.P. (1998). Market Simulations via Rule Induction: A Machine Learning Approach. In: Zopounidis, C., Pardalos, P.M. (eds) Managing in Uncertainty: Theory and Practice. Applied Optimization, vol 19. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2845-3_18
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DOI: https://doi.org/10.1007/978-1-4757-2845-3_18
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