A risk classification method for contract performance based on G1-improved entropy weight two-dimensional cloud model
Yufeng Ma, Dong Huang, Yuhua Wang · Advances in Complex Systems · 2025
Traditional risk classification approaches often fail to simultaneously address the intrinsic correlations among indicators and the optimism level of decision-makers regarding the evaluation object. To resolve this issue, a novel risk classification method for equipment procurement contract performance is presented, based on a G1-improved entropy weight two-dimensional cloud model. Initially, subjective weights are determined using the order relation analysis method (G1 method). Objective weights are then derived through an enhanced entropy weight method that incorporates the Criteria Importance Through Intercriteria Correlation (CRITIC) approach to reflect inter-indicator dependencies. The moment estimation method integrates these subjective and objective weights. Subsequently, the conventional two-dimensional cloud model is refined by introducing the Ordered Weighted Geometric Averaging (OWGA) operator, enabling the direct inclusion of decision-makers’ optimism toward the evaluation object. This integrated model facilitates a more accurate evaluation of contract performance risks, reducing the distortion in outcomes typically caused by one-sided closeness calculations in traditional models. A case analysis validates the method’s scientific robustness and practical applicability.