Evaluating the capacity of paired comparison methods to aggregate rankings of separate groups.

Ranking and rating methods have outstanding significance in sports, mainly due to their capacity to predict results. In this paper we turn to their capacity to aggregate separate groups' rankings based on a small piece of information. We investigate under which conditions two or more separate groups can be trustworthily interwoven applying Thurstone motivated methods and an AHP based method.

Analyzing and clustering students' application preferences in higher education.

We present a framework based on a higher education application preference list that allows a different type of flexible aggregation and, hence, the analysis and clustering of application data. Preference lists are converted into scores. The proposed approach is demonstrated in the context of higher education applications in Hungary over the period of 2006-2015.