E-democracy provides a virtual online platform characterized by information transparency and equal interaction, which facilitates the participation of multiple agents in government decision-making. This chapter proposes a comprehensive loss analysis-based decision support method and applies it to a case study of e-democratic multi-agent cooperative decision-making. Multiple agents represent different interests and provide opinions with the goal of maximizing their own revenues. The agents’ opinions are naturally prone to differences and even conflicts, which may have a negative impact on the harmony of the social system. To this end, this chapter develops a two-stage type- \(\alpha \) constrained minimum-revenue-loss consensus (TS- \(\alpha \) -CMRLC) model. In Stage 1, an \(\alpha \) -CMRLC model is adopted to obtain the optimal solutions of agents’ opinions with minimizing the social revenue loss and preventing excessive revenue loss. In Stage 2, the concept of reputation loss is defined and an \(\alpha \) -CMRLC model considering reputation loss is proposed. In this matter, the high-reputation but low-consensus agent can reduce its revenue loss through the cost of reputation loss. The research results show that an increase in some agents’ reputation losses leads to a decrease in their revenue losses, but it may cause an increase in the social revenue loss. We perform a comprehensive loss analysis to evaluate the performance of reputation loss. Finally, the comparative analysis reveals the feasibility and advantages of the proposed method.