An ordinal regression approach for analyzing consumer preferences in the art marketAn ordinal regression approach for analyzing consumer preferences in the art market Peer-Reviewed Journal Publication Δημοσίευση σε Περιοδικό με Κριτές 2022-04-142021enInnovative Applications of O.R.From its origin at the Renaissance, the art market is part of the global economy. Arts and cultural production add significant real values on the Gross Domestic Product (GDP) of several countries and a strong symbolic contribution in prestige for owners, either private collectors or cities and countries. The significant price fluctuations that may be observed in the market of artistic goods can be explained not only by the uniqueness of works of art and the economic conditions, but also by the changing preferences of buyers. The main aim of this paper is to develop an ordinal regression analysis model for studying the preferences of artistic goods buyers. The applied approach assumes that the price of a work of art depends on a set of criteria aiming to infer additive value functions that aggregate these criteria in such a way that these functions are optimally consistent with a given price. The presented study uses a large set of auction data from the Art Deco furniture market and considers several different criteria that may influence buyers’ preferences. These criteria are related to the physical or intangible characteristics of artistic goods. The results are mainly focused on analyzing buyer's preferences (e.g., contribution of several factors to the price of artistic goods), while the ordinal regression model has been applied in different time periods in order to study how preferences evolve over time. Finally, stability analysis has been performed, with the aim of evaluating the robustness of the results.http://creativecommons.org/licenses/by/4.0/European Journal of Operational Research2902718–733 Grigoroudis Evangelos Γρηγορουδης Ευαγγελος Noel Laurent Galariotis, Emilios Zopounidis Konstantinos Ζοπουνιδης Κωνσταντινος Elsevier Multiple criteria analysis Ordinal regression Art market Investor behavior Auction data