An application of z-number theory based multi choice bwm, copras and rafsi to evaluate carbon footprint calculators

Advanced MCDM techniques are becoming more and more necessary in today's multifaceted and uncertain decision making contexts, when conventional approaches are insufficient. The Z-number method facilitates more realistic outcomes by integrating both the assessments of decision makers and their confidence levels in these assessments into the model. The MC-BWM, an extension of the traditional BWM, provides flexibility by enabling decision makers to choose several best and worst criteria. The COPRAS technique, employed for alternative ranking, delivers a comprehensive and relevant ranking by concurrently evaluating both benefit and cost factors. Conversely, the RAFSI method facilitates the efficient ranking of alternatives through the functional synthesis of criterion weights and performance values. The amalgamation of these methodologies significantly enhances decision making processes, especially in domains marked by considerable uncertainty, including sustainability, environmental impact assessment, and supply chain management. To determine criteria weights, this study used the MC-BWM, which is based on Z-number theory. Subsequently, all corporate carbon footprint calculator alternatives were ranked using the COPRAS and RAFSI techniques. This method enables decision makers evaluating the corporate carbon footprint to allocate different weights to criteria and provides a reliable rating with considerable distinctiveness.