PAIRWISE COMPARISON MATRIX IN MULTIPLE CRITERIA DECISION MAKING

TLDR

The pairwise comparison matrix (PCM) has been extensively studied for measurement scales, consistency, inconsistency, missing judgments, and priority derivation, with various approaches contributing to decision making. The study reviews and classifies recent PCM literature to identify current hot topics, techniques, and future research directions. The review focuses on 37 peer‑reviewed international journal articles published between 2010 and 2015, identified via ISI Web of Science. The review offers a comprehensive summary of PCM developments, serving as a guide for future research.

Abstract

The measurement scales, consistency index, inconsistency issues, missing judgment estimation and priority derivation methods have been extensively studied in the pairwise comparison matrix (PCM). Various approaches have been proposed to handle these problems, and made great contributions to the decision making. This paper reviews the literature of the main developments of the PCM. There are plenty of literature related to these issues, thus we mainly focus on the literature published in 37 peer reviewed international journals from 2010 to 2015 (searched via ISI Web of science). We attempt to analyze and classify these literatures so as to find the current hot research topics and research techniques in the PCM, and point out the future directions on the PCM. It is hoped that this paper will provide a comprehensive literature review on PCM, and act as informative summary of the main developments of the PCM for the researchers for their future research.