Large group decision-making incorporating decision risk and risk attitude: A statistical approach

Abstract

In this study, we propose a statistical method incorporating decision risk and risk attitude into large group decision-making. The decision-making groups are divided into subgroups based on their attitudes to risk, and the evaluation information for the decision-makers within the same subgroup is combined to form the sample dataset. Next, the internal decision risk levels of all subgroups are measured using sample standard deviations and reduced through a feedback mechanism. Significance testing is used to determine the criterion weights and to measure the external decision risk levels of subgroups. The internal and external decision risk levels are then combined to yield the subgroup weights. Confidence interval is used to transform the sample data into interval numbers, which are then aggregated and analyzed to yield the decision-making results. Meanwhile, risk attitudes are taken into account throughout the decision-making process by various means. A case study and comparison analyses, along with sensitivity analyses, are used to illustrate the feasibility and rationality of the proposed method. Our experiments suggest that decision risk and risk attitude matter in large group decision-making.