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A fuzzy multiple-attribute decision making model to evaluate new product pricing strategies

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Abstract

The aim of this paper is to provide a new fuzzy Multiple-Attribute Decision Making model for evaluating product pricing strategies. The problem is structured in a hierarchical setting. Possible interactions and interdependencies among hierarchically structured criteria are taken into consideration. Since new product pricing decisions entail decision makers’ uncertain judgments concerning many interacting factors, Fuzzy Cognitive Maps are employed to analyze causal dependencies among attributes. Finally, decision makers’ linguistic assessments are transformed into ranking orders of the pricing strategies using the Technique for Order Preference by Similarity to Ideal Solution. The proposed model is implemented in a Turkish software company. The case study has showed that the proposed model is practical and easy to apply. The proposed model can be incorporated into marketing strategies of wide variety of new products.

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  1. Department of Industrial Engineering, Faculty of Engineering, Dokuz Eylül University, Izmir, Turkey

    Adil Baykasoğlu, İlker Gölcük & Derya Eren Akyol

  2. The Graduate School of Natural and Applied Sciences, Dokuz Eylül University, Izmir, Turkey

    İlker Gölcük

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  1. Adil Baykasoğlu
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Correspondence to Adil Baykasoğlu.

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Baykasoğlu, A., Gölcük, İ. & Akyol, D.E. A fuzzy multiple-attribute decision making model to evaluate new product pricing strategies. Ann Oper Res 251, 205–242 (2017). https://doi.org/10.1007/s10479-015-1895-4

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