Best-Worst Method: Inconsistency, Uncertainty, Consensus, and Range Sensitivity

It is our choices that make us who we are. To lead a better life, we have to make better decisions. Nowadays, decisions are increasingly made in complex contexts, in a host of different application domains. Because of that, we need more reliable decision analysis methodologies to improve our decisions. The ability to deal with multi-dimensionality is one of the critical requirements of the decision analysis methods that help us make better decisions. Multi-Criteria Decision-Making (MCDM) is one of the most popular approaches when it comes to formulating and solving decision-making problems, best-known for its ability to handle problems where a multitude of, often conflicting, criteria arise. As one of the latest MCDM methods, the Best-Worst Method (BWM) has been studied substantially and applied increasingly to various fields since its introduction, thanks to its simplicity, flexibility and general applicability. Despite its popularity, some significant issues of BWM have not yet been systematically investigated in existing literature, including: (i) the inconsistency in the preferences provided by Decision-Makers (DMs), (ii) the uncertain information embedded in the DMs’ judgements, (iii) problems in reaching a consensus in group decision-making, and (iv) the range sensitivity in an MCDM problem that is not taken into account in BWM. The main objective of this thesis is to develop an approach to measure, check and improve inconsistency, to develop an approach to incorporate judgments uncertainty, to develop a method to reach consensus and to incorporate range sensitivity in the BWM.