Abstract
In marketing decision support systems (MDSSs), basic information is obtained through market surveys and, to some extent, by using appropriate marketing models. Marketing models with MDSSs may represent the responses of the market to the various actions of the decision-makers. In this way, decision-makers and marketers can predict the reactions of the customers before trying to push a product in the market. In this chapter, an MDSS is presented. This MDSS has a user-friendly and easy-to-learn, menu-driven interface. The purpose of this MDSS is to assist a marketer in designing a new product when the customer preferences are not compensatory. The MDSS uses the share of preference frequency criterion. In this criterion, the new product is determined to maximize the relative preference frequency at which customers choose the new product. The MDSS examines different scenarios using the ‘‘what if analysis’’. Additionally, the MDSS finds near-optimal solutions for realistically sized problems using evolutionary algorithms. It is not necessary for the user to be familiar with the underlying models. A case study that applies the MDSS to the design of a new product for a Mexican company is presented.
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Leyva López, J.C., Figueroa Pérez, J.F., Pérez Contreras, E.O., Sánchez Sánchez, P. (2020). A Marketing Decision Support System for Product Design Based on an Outranking Approach. In: Kahraman, C., Cebi, S. (eds) Customer Oriented Product Design. Studies in Systems, Decision and Control, vol 279. Springer, Cham. https://doi.org/10.1007/978-3-030-42188-5_16
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