A new integrated intuitionistic fuzzy group decision making approach for product development partner selection


COMPUTERS & INDUSTRIAL ENGINEERING, vol.102, pp.383-395, 2016 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 102
  • Publication Date: 2016
  • Doi Number: 10.1016/j.cie.2016.05.038
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.383-395
  • Keywords: Intuitionistic fuzzy group decision making, Product development partner selection, Intuitionistic Fuzzy AHP, Intuitionistic Fuzzy TOPSIS, ANALYTIC HIERARCHY PROCESS, SUPPLIER SELECTION, TOPSIS, MODEL, AHP, INFORMATION, MULTIPERSON, PERFORMANCE, OPERATORS, SYSTEM
  • Galatasaray University Affiliated: Yes


Globally, customers are getting increasingly demanding in terms of quality, price and performance of products and are asking for shorter product development periods with more predictable cycles. These market pressures drive firms to collaborate with possible partners in product development (PD) processes. Nevertheless, choosing the suitable partner for an effective PD is a challenging, complex decision. This study proposes a combined Intuitionistic Fuzzy (IF) Group Decision Making (GDM) model that consists of the Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) and Intuitionistic Fuzzy Technique for Order Preference by Similarity to Ideal Solution (IF-TOPSIS) methods for effectively evaluating PD partners. In order to obtain a more complete evaluation and more precise results, IF-AHP is used for determining criteria weights, whereas IF-TOPSIS methodology is conducted for ranking partner alternatives. This study contributes to partner selection and IF set literature by providing a combined framework based on IF-AHP and IF-TOPSIS with GDM methodology for the first time. To assess the validity of the proposed integrated IF GDM approach, a case study is also provided. This study contributes to literature as it provides a better insight into the theoretical ground of the PD partner selection problem. It also supports organizations which aim to improve their PD evaluation systems. (C) 2016 Elsevier Ltd. All rights reserved.