Fuzzy Consensus Qualitative Risk Analysis Framework for Real Estate Projects

Abstract

This paper presents a fuzzy consensus qualitative risk analysis framework to identify and prioritize risks encountered in real estate projects. The framework incorporates consensus and quality of experts in the process of evaluating risk events and it is composed of a fuzzy expert system to determine qualification of experts; a fuzzy distance measurement algorithm to aggregate experts' opinions; and a three-dimensional prioritization approach to rank the risks. A case study incorporates a three-step Delphi technique to collect experts' opinions and compares them to the outputs of the model. The framework identifies and evaluates real estate risks in a fully supported linguistic environment, using fuzzy logic, which addresses the vagueness and imprecision that exist in the decision-making process. It provides an improvement over qualitative risk assessment models by applying the qualification of experts in aggregating their opinions, using FES, instead of relying on an arbitrary assessment of experts' qualifications; and it also modifies fuzzy consensus aggregation algorithms by enabling the aggregation of non-overlapping opinions and applying it to the risk prioritization process.