# A Multiple Criteria Decision Analysis Framework for Dispersed Group Decision-Making Contexts
## 6 Conclusions and Future Work  
To support GDM processes when participants are dispersed is a complex task. There are several approaches that consist of proposing possible solutions according to the decision-makers' preferences. However, this is the greatest and sometimes the only concern of the big majority. Such a vision impedes decision-makers to benefit from the recognized advantages associated with GDM processes. In addition, a GDSS that recommends or proposes actions to decision-makers, without being capable of justifying or presenting the necessary information that supports those recommendations or proposals, can transform them into a source of entropy. In this paper, we propose a Multiple Criteria Decision Analysis Framework that intends to become an important tool for researchers and developers that are interested in developing MCDA methods or consensual approaches to support GDM processes with geographically dispersed participants. The proposed framework was designed to allow the deduction and understanding of the reasons behind the different recommendations or proposals. In addition, it allows the inclusion of several aspects that are important in the GDM context, such as expertise level, credibility, behavior styles, and decision quality prediction. In order to validate and study the potential of the proposed MCDA framework, a set of application scenarios were tried in experiments. The experiments consisted of analyzing whether the framework had the resources to perform a set of tasks essential to support a GDM process that promotes the decision-makers' interaction and enhances decision quality, reducing potential entropy sources and allowing decision-makers to benefit from the fact that they are deciding in group. The experiments showed that the proposed framework allows to deduce the reasons why possible proposals or recommendations are made. In addition, it was found that different strategies can be used to accomplish the same task and that a strategy can result in different outcomes. An example is the case where an alternative is proposed as a solution by calculating the group predicted satisfaction or by using the consistency method, which, on either case, originates different justifications for the same task. We also developed a microservice to expose the framework's functionalities as resources. The developed microservice is part of a Consensus-based Group Decision Support System which has other microservices for different businesses. The developed microservice was used to feed two other microservices each one containing a multi-agent system, where the agents used the framework to get new knowledge to use in their own dialogues and to support decision-makers with personalized  
Figure 7: Elements of the “Personal Information” screen. information. As was evidenced in the experiments, the framework provides a lot of different and relevant information, being easy to use by other software clients. The developed microservice was also used in the consensus reaching process in order to propose solutions and alternatives to reject, decreasing the decision's complexity. We also concluded that the inclusion of the strategy for predicting the importance of the criteria from the perspective of each decision-maker, as well as the relevance that each criterion has for each alternative, enables the development of future important strategies, both for the creation of recommendations and the perception of the motives that lead to those recommendations. In addition, it provides a very clear view of possible inconsistencies in the evaluation made by decision-makers regarding the importance of alternatives and criteria. The use of the consistency strategy has also shown to play an important role in what the creation of alerts might be, as well as in identifying possible incorrect or subjective assessments. The generated alerts can therefore help decision-makers to correct certain assessment \"mistakes\".