Quantum group decision-making approach for green supplier selection featuring virtual character-involved consensus mechanism and interference effect

As global environmental issues become increasingly severe, green supplier selection (GSS) has a direct bearing on the effectiveness of enterprises’ sustainable development strategies. While, the existing emerging methods are difficult to fully address the challenges faced in the process of GSS, such as uncertainty, consensus reaching, criterion interaction and group interference effect. In this regard, this study proposes a novel quantum group decision-making approach with virtual character-involved consensus mechanism for selecting green supplier. First, probabilistic uncertainty linguistic terms are used by experts to express their preferences in response to uncertainty. Then, for ensuring the effectiveness of preference information, a virtual character-involved consensus mechanism is designed to optimize group structure, which considers the stability and the original value information protection. Meanwhile, based on the emotional tendency of experts, a two-stage PT-whitening approach is proposed to calculate criteria weights. Additionally, a two-layer quantum-like Bayesian network is constructed to compute the quantum probabilities of green suppliers and rank them, while utilizing a new hybrid method to address the interference terms in the quantum probabilities. Finally, the presented approach is applied to an illustrative case, and the outcomes are shown to be beneficial and efficacious by sensitivity and comparison analyses. Results of the study indicate that candidate green suppliers are not sensitive to economic benefit compared to other criteria. The key implications further lay the foundation for promoting the decision support field and the enterprises’ sustainable development practice.