SocialPort

The Delphi survey is an opinion convergence method that is achieved in a sequence of steps. It refers to carrying out successive research steps, carried out with experts. Its objective is to obtain convergence of opinion regarding numerical values, such as, for example, the probability of occurrence of a future event or future expectations in relation to the value of an indicator. This convergence is stimulated by the median value indicated at each stage by the participants.

At SocialPort, all execution steps seek to speed up results. Therefore, sending invitations, starting new stages and calculating medians are all automatic. Another difference concerns the user experience, as the questions presented are only those that have not yet achieved convergence, reducing the number of questions to be answered at each stage.

Research that aims to identify important events with a high degree of uncertainty. This is done with a numerical scale of importance, with 1 being irrelevant and 5 being very important, and with an uncertainty value converted from the probability of the event occurring.

The research takes place in a single round, in which experts indicate the two values ​​mentioned above for each event. On the Dashboard, de Importance X Uncertainty chart is displayed, in addidtion to charts referring to each event, with all the resulting descriptive statistics.

Research that aims to verify the capacity for direct and indirect interference of event V1 on other events (Vn) that constitute the system object of the study. This is done by filling in a matrix, in which the value of a field corresponds to the ability of a certain event, described in a row, to interfere with the occurrence of other events described in the columns.

The Dashboard presents the Motricity X Dependence chart, the matrix filled with the average of the values ​​obtained from the respondents and a calculator that allows identifying the motricity and dependence values ​​of each variable at higher levels of interference.

The tool aims to verify the degree of influence that each actor has on the variables. This is done by filling in a matrix in which each cell refers to the impact that the actor (column) has on the variable (row).

The result is presented as a ranking of the most influential actors in the system.

The importance of actor analysis is based on the fact that no variable moves or changes the course of its behavior if there is no actor influencing this movement.