The selection process of team leaders is fundamental if the effectiveness of teams is to be guaranteed. Human values have proven to be an important factor in the behaviour of individuals and leaders. The aim of this study is twofold. The first is to validate Schwartz's survey of human values. The second is to determine whether there are any relationships between the values held by individuals and their preferred roles in a team. Human values were measured by the items of the Schwartz Value Survey (SVS) and the preferred roles in a team were identified by the Belbin Self Perception Inventory (BSPI). The two questionnaires were answered by two samples of undergraduate students (183 and 177 students, respectively). As far as the first objective is concerned, Smallest Space Analysis (SSA) was performed at the outset to examine how well the two-dimensional circular structure, as postulated by Schwartz, was represented in the study population. Then, the results of this analysis were compared and contrasted with those of two other published studies; one by Schwartz (2006) and one by Ros and Grad (1991). As for the second objective, Pearson correlation coefficients were computed to assess the associations between the ratings on the SVS survey items and the ratings on the eight team roles as measured by the BSPI.

The present study explores the usefulness of dyadic quantification of group characteristics to predict team work performance. After reviewing the literature regarding team member characteristics predicting group performance, percentages of explained variance between 3% and 18% were found. These studies have followed an individualistic approach to measure group characteristics (e. g., mean and variance), based on aggregation. The aim of the present work was testing whether by means of dyadic measures group output prediction percentage could be increased. The basis of dyadic measures is data obtained from an interdependent pairs of individuals. Specifically, the present research was intended to develop a new dyadic index to measure personality dissimilarity in groups and to explore whether dyadic measurements allow improving groups' outcome predictions compared to individualistic methods. By means of linear regression, 49.5 % of group performance variance was explained using the skewsymmetry and the proposed dissimilarity index in personality as predictors. These results support the usefulness of the dyadic approach for predicting group outcomes.