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Market simulations via rule induction: A machinelearning approach

Matsatsinis Nikolaos, Samaras Andreas

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URIhttp://purl.tuc.gr/dl/dias/AFAB0BA5-BBC0-42EF-BA63-F30486E56C68-
Identifierhttps://doi.org/10.1007/978-1-4757-2845-3_18-
Languageen-
TitleMarket simulations via rule induction: A machine learning approachen
CreatorMatsatsinis Nikolaosen
CreatorΜατσατσινης Νικολαοςel
CreatorSamaras Andreasen
CreatorΣαμαρας Ανδρεαςel
PublisherSpringer Verlagen
Content SummaryNew 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.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-20-
Date of Publication1998-
Bibliographic CitationMatsatsinis, N.F., A.P. Samaras, "Market Simulations via Rule Induction: A Machine Learning Approach", Managing in Uncertainty: Theory and PracticeVol. 19, pp. 261-274, 1998. DOI 10.1007/978-1-4757-2845-3_18en

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