Intuitionistic Fuzzy Decision Making Towards Efficient Team Selection in Global Software Development

Abstract

For successful completion of any software project, an efficient team is needed. This task becomes more challenging when the project is to be completed under global software development umbrella. The manual selection of team members based on some expert judgment may lead to inappropriate selection. In reality, there are hundreds of employees in an organization and a single expert may be biased towards any member. Thus, there is a need to adopt methods which consider multiple selection criteria with multiple expert views for making appropriate selection. This article uses an intuitionistic fuzzy approach to handle uncertainty in the expert's decision in multicriteria group decision making process and ranking among the finite team members. An intuitionistic fuzzy Muirhead Mean (IFMM) is used to aggregate the intuitionistic criteria's. To gain confidence between criteria and expert score relationship, the Annova test is performed. The results are promising with p value as small as 0.02 and one-tail t-test score equals to 0.0000002.