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

Collaborative Network (CN) as a new emerging paradigm can rapidly answer market demands by eective collaboration and coordination between enterprises. Nowadays, it has become a potential solution for dierent organizations to manage their business issues eectively. 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 proposes 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. Then, a hybrid approach is designed to integrate Intuitionistic Fuzzy Ordered Weighted Averaging (IFOWA) operators into the a Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) procedure. Moreover, 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 by the matching factor. The result shows that ranking the solutions for forming CN is relatively sensitive to the matching factor