Contrasting Voting, Multi-criteria Decision-Making, and Collaborative Decision-Making Using Election Results

Improving decision-making requires examining and applying effective techniques. This paper contrasts three decision-making approaches using primary election results as a baseline. Election voting, multi-criteria decision analysis (MCDA), and collaborative decision-making (CDM) capitalizing on collective intelligence are compared to evaluate the utility of the approach along with the benefits and issues with each. The CDM approach was significantly more effective at improving the decision-making process by providing a rich dataset for the analysis of alternatives. An open, collective intelligence process demonstrates the potential for eliciting both evaluation criteria and decision alternatives to increase the efficacy of the decision analysis and potential for identifying an optimal decision alternative.