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

Adil Baykasoğlu (), İlker Gölcük and Derya Eren Akyol
Additional contact information
Adil Baykasoğlu: Dokuz Eylül University
İlker Gölcük: Dokuz Eylül University
Derya Eren Akyol: Dokuz Eylül University

Annals of Operations Research, 2017, vol. 251, issue 1, No 13, 205-242

Abstract: 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.

Keywords: New product pricing; Fuzzy cognitive maps; Hierarchical fuzzy TOPSIS; MADM (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://link.springer.com/10.1007/s10479-015-1895-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:251:y:2017:i:1:d:10.1007_s10479-015-1895-4

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-015-1895-4

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().