Air cargo company selection under a state of chaos: An integrated bayesian BWM and WASPAS approach

ABSTRACT

Depending on whether or not there is a chaotic condition, the outcomes of decision problems and the factors determining the outcomes of the problem may differ. Different criteria can be introduced for decision makers' preferences in chaotic conditions, and the importance levels of the criterion can fluctuate. Despite the fact that the COVID-19 epidemic has had an impact on the aviation industry, air cargo transportation has performed well during this time. From this perspective, the impact of chaotic events on the selection of an air freight firm is investigated in this study. With Multi-Criteria Decision Making (MCDM) methodologies, a new decision-making framework is proposed, which is an effective solution method for choice makers to finalize decision problems. The Bayesian BWM (Best-Worst) method, which is one of the new ways, is used to establish the criterion weights, while the WASPAS method is utilized to rank the air cargo businesses, due to the more sensitive reaction of the newly proposed methods. As a result, these two approaches are combined, and the ranking results are compared to the TOPSIS and COPRAS methods, with the outcomes examined. As a result, in a chaotic environment, the most essential consideration for selecting an air freight company appears to be economic criteria. © 2023 Gazi Universitesi Muhendislik-Mimarlik. All rights reserved.