Advancing individual decision-making: An extension of the characteristic objects method using expected solution point

Abstract

This study introduces an extension of the Characteristic Objects Method (COMET) by incorporating the Expected Solution Point (ESP) approach to enhance individual decision-making. By integrating the ESP methodology, we aim to simplify decision-making, particularly when facing a vast decision matrix concerning multiple criteria. We demonstrate the efficacy of the proposed ESP-COMET method by applying it with one or two ESPs, thereby examining its impact on ranking alternatives according to personal customer preferences. In order to provide a practical example, we use a dataset of used cars to show how the proposed method facilitates the selection of the most suitable vehicle based on individual needs. The main goal of this paper is to show how the ESP-COMET method can help to adapt decisions to individual needs and expectations. We also introduce a novel and efficient approach for determining characteristic values in personalized decision-making, which plays a crucial role in ensuring the higher accuracy of the ESP-COMET method. Additionally, we compare the proposed approach with such methods as Stable Preference Ordering Toward the Ideal Solution (SPOTIS) and Reference Ideal Method (RIM). This study addresses the research gap by introducing an easy way to define customer preferences within COMET, enabling responsible decision-making.

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