A general Best-Worst method considering interdependency with application to innovation and technology assessment at NASA
The Best-Worst Method (BWM) is a relatively new and popular method for obtaining criteria weights in multi-criteria decision-making. The BWM uses very few comparisons and produces consistent comparisons, leading to more reliable criteria weights. Despite its popularity and reliability, the decision criteria in the BWM are considered independent of one another. However, in most real-world problems, the decision criteria are interdependent. We propose a general form of the BWM (GBWM) to consider the interdependencies and the intensity of the dependencies among the decision criteria in producing relative influence-intensity weights. The new GBWM is simple to understand and implement and delivers reliable results with a high level of consistency in problems with interdependent decision criteria. The results are more reliable than BWM in problems with interdependencies because we consider both their existence and the intensity of the dependencies. In addition, the results are equally or more consistent than BWM because we start with a BWM solution and adjust the BWM solution with a completely consistent vector. We also present a case study for evaluating and prioritizing advanced technology and innovation projects at NASA to demonstrate the applicability of the proposed method.
Tavana, Madjid; Mina, Hassan; and Santos-Arteaga, Francisco, "A general Best-Worst method considering interdependency with application to innovation and technology assessment at NASA" (2022). Business Systems and Analytics Faculty Work. 337.