Ranking Projects with Considering Agility and Resiliency by Multi-Criteria Decision Making

Project agility and resiliency are two important qualities that can help projects to succeed in uncertain and dynamic environments. Agile projects are able to adapt to change quickly and efficiently, while resilient projects are able to withstand and recover from disruptions. Multi-criteria decision making (MCDM) is a method for evaluating and ranking projects based on multiple criteria. It can be used to rank projects by considering both their agility and resiliency. This paper presents a review of the literature on project agility, resiliency, and MCDM. It also proposes a new MCDM framework for ranking projects with considering agility and resiliency. The framework is applied to a case study of three software projects to demonstrate its feasibility and effectiveness. The results show that the framework can be used to successfully rank projects by considering both their agility and resiliency. This can help organizations to select the projects that are most likely to succeed in uncertain and dynamic environments.Project agility and resiliency are two important qualities that can help projects to succeed in uncertain and dynamic environments. Agile projects are able to adapt to change quickly and efficiently, while resilient projects are able to withstand and recover from disruptions. Multi-criteria decision making (MCDM) is a method for evaluating and ranking projects based on multiple criteria. It can be used to rank projects by considering both their agility and resiliency. This paper presents a review of the literature on project agility, resiliency, and MCDM. It also proposes a new MCDM framework for ranking projects with considering agility and resiliency. The framework is applied to a case study of three software projects to demonstrate its feasibility and effectiveness. The results show that the framework can be used to successfully rank projects by considering both their agility and resiliency. This can help organizations to select the projects that are most likely to succeed in uncertain and dynamic environments.