An intuitionistic fuzzy OWA-TOPSIS method for collaborative network formation considering matching characteristics

Abstract

Collaborative network (CN) as a new emerging paradigm can rapidly answer market demands by effective enterprise collaboration and coordination. Nowadays, it has become a potential solution for different organizations to manage their businesses effectively. Thus, selecting a suitable partner combination is critical to CN success. Matching characteristic is very important for partner combination selection in the CN formation, while it is neglected in the existing research. This paper is to propose a method and model for partner combination selection of CN considering matching utility. Firstly, the matching factors are developed from four aspects, supply capability, goal, culture and technology. And then a hybrid approach is designed to integrate intuitionistic fuzzy Ordered Weighted Averaging (IFOWA) operators into the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) procedure. And matching utility combination method amongst multi-partners is advanced to establish the partner combination model. Moreover, a decision support system is applied in a practical enterprise to illustrate the advantage of the proposed method. Finally a sensitivity analysis is conducted to investigate the robustness of solutions ranking to changes in matching factor. The result shows that ranking the solutions for forming CN is relatively sensitive to its matching factor.