A hybrid multi-attribute decision-making procedure for ranking project proposals: A historical data perspective

This paper develops a hybrid multiattribute decision-making methodology for ranking project proposals (PPs) through a judicious usage of historical data of completed projects to determine attribute weights, enabling elimination of problems associated with projected data such as cost and schedule overruns of real-world projects. The weights generated from data envelopment analysis are explicitly utilized for ranking PPs while allowing subjectivity to be ingeniously incorporated into the decision process. The new approach is implemented for ranking 25 PPs, and the rankings it yields are found indifferent to the decision maker's attitude, which ascertains the robustness of the ranking methodology.     

A systematic approach for ranking football players within an integrated DEA‐OWA framework

The ranking of players has always been an important input for key decisions in the football industry. This paper introduces a systematic methodology for ranking football players through objective performance factors within a framework that integrates data envelopment analysis and ordered weighted averaging operators. Players from European Premier League Football clubs are selected and ranked under a decision setting that involves the players' desirable and undesirable performance factors alongside the attitude of the decision maker. The robustness of the proposed methodology is evaluated using different levels of optimism of the decision maker.