An integrated multicriteria group decision making methodology for property concealment risk assessment under Z-number environment

Abstract

The complexity and opacity of individual property concealment seriously impede the court's judicial execution. Property concealment risk assessment can assist law enforcement officers in predicting the probability of judgment debtor’s concealment behavior in advance and improve enforcement efficiency. However, few studies have explored the property concealment risk assessment from the perspective of qualitative multicriteria decision making, considering the uncertainty of expert’s evaluation and the non-complementarity between assessing criteria. To fill this gap, we propose a novel integrated multicriteria group decision-making methodology (MCGDM) under the Z-numbers environment to rank the concealing risk of judgment debtors. First, Z-numbers are employed to characterize the uncertainty and reliability of cognitive information simultaneously. Next, we present an expert weight determining method based on the degree of group consistency and reliability under the Z-numbers environment (WCRZ). Then, an innovative score function is presented, extending the ELECTRE- III method to Z-number environment to obtain individual outranking relations. Moreover, we develop the weighted Copeland method to aggregate individual rankings and obtain comprehensive risk prioritizations. Finally, an application case in concealing property risk ranking illustrates the proposed method. Results show that the proposed method can be successfully applied to practical complex decision-making problems, and it obtains more reasonable outcomes than conventional methods, with lower computational complexity and higher group consensus. It is the first study to model the concealing risk of judgment debtors, and the proposed method can be employed to address complex, uncertain decision problems in the real world.