A novel 2-phase consensus with customized feedback based group decision-making involving heterogeneous decision-makers

In Group Decision-Making (GDM), decision-makers (DMs) who are experts take wise decisions. But in systems such as smart cities, IoT, and e-democracy, the acceptance and survival of the decision given by the experts depend on the experience of citizens and end-users. Hence, an attempt can be made to use the citizens' perceptions. A potential solution to improve the acceptance and survival of the decision is to include citizens' opinions too in the decision-making. In this work, a novel GDM model is proposed that involves non-experts along with the experts to understand the opinions of non-experts also by the experts. Two phases of the consensus reaching process (CRP) are defined: the inter-consensus reaching phase, where consensus between experts and non-experts will be achieved, and the intra-consensus reaching phase, where the experts negotiate among themselves to attain the consensus. In existing GDM models, CRP overcomes the conflicts in the opinions of the DMs by providing feedback to DMs for modifying their preferences to achieve the required consensus. However, multiple feedback rounds increase the cost of CRP. The proposed GDM gives customized feedback to the experts only once at each phase, reducing the feedback cost in attaining the consensus. A numerical example is discussed to explain the effectiveness of the proposed model. The proposed approach is tested on different consensus thresholds to verify its practicality.