Smart group decision making on leadership style identification using bayes theorem

Abstract

The un-synergistic criteria’s of the candidate and the organization’s vision and mission became the main problem. The subjectivity of certain group tended to bring the frustration hence it provoked the emergence of conflict interests. In order to cover such issues, this paper proposed the blending of an expert system using Bayes theorem and Group Decision Making in identifying the candidate’s leadership style. The analysis was conducted in a series of activities through the development of knowledge base, inference engines, weighting, experts’ alliance, decision tree diagram, intersection independent and mean sample calculation. As a result, eleven numbers of leadership styles were theoretically identified thus confirmed and weighted by experts. In addition, the correlation between the leadership style and organizational vision and mission was analyzed. The leaders’ assessments were perceived by the candidate itself and supported team members. The calculation of estimated values proposed the percentage of candidate leadership style identification. This provided a smart group decision making in recommending organizational decision-makers towards the fit proper elected leader based on the situation. To automate the calculation, prototype assessment software was produced and tested. Black-box and User Acceptance Test found that this application was successfully applied in identifying the leadership style for future leaders.