https://hal-emse.ccsd.cnrs.fr/emse-00673983Dolgui, AlexandreAlexandreDolguiLaboratoire en Sciences et Technologies de l'Information - MSGI-ENSMSE - Département Méthodes Scientifiques pour la Gestion Industrielle - Mines Saint-Étienne MSE - École des Mines de Saint-Étienne - IMT - Institut Mines-Télécom [Paris] - Centre G2IProth, Jean-MarieJean-MarieProthINRIA Lorraine - Inria - Institut National de Recherche en Informatique et en AutomatiquePricing strategies and modelsHAL CCSD2010Conjoint measurementCost-plus methodDiscount strategyDuopoly marketHigh price strategyLow price strategyMarginMarket segmentationPart-worthPenetration pricingPrice skimmingPrice testingRevenue managementSalvage valueSelling curve[SDE.ES] Environmental Sciences/Environmental and SocietyBreuil, Florent2021-11-26 18:01:152023-02-28 15:36:242021-12-10 16:34:30enJournal articleshttps://hal-emse.ccsd.cnrs.fr/emse-00673983/document10.1016/j.arcontrol.2010.02.005application/pdf1Price is a major parameter that affects company revenue significantly. This is why this paper starts by presenting basic pricing concepts. Strategies, such as market segmentation, discount, revenue management, price skimming, are introduced. A particular attention is paid to the relationship among margin, price and selling level. Then, the impact of prices on selling volume is analyzed, and the notion of selling curve is introduced. Related pricing methods are discussed such as price testing, cost-plus method, involvement of experts, market analysis and customer surveying. Included in the last category is the conjoint measurement concerned with finding what parameters of the items are important to customers. The profile method and a simplified version, the two-factor method, are also detailed. They provide a set of part-worths (i.e., numerical values) for each tester. In other words, the opinion of each tester can be represented by a point in a space whose dimension is the number of part-worths. By applying a clustering method, specifically K-mean analysis, a limited number of clusters can be obtained, each of them representing a market segment. A deterministic pricing model with time-dated items is also analyzed. This model provides practical insights into pricing mechanisms.