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Predicting Team Output Using Indices at Group Level

Published online by Cambridge University Press:  10 January 2013

Amara Andrés*
Affiliation:
Universidad de Barcelona (Spain)
Lluís Salafranca
Affiliation:
Universidad de Barcelona (Spain)
Antonio Solanas
Affiliation:
Universidad de Barcelona (Spain)
*
Correspondence concerning this article should be addressed to Amara Andrés, Departamento de Metodología de las Ciencias del Comportamiento, Facultad de Psicología, Universidad de Barcelona, Paseo Vall d'Hebron 171, 08035, Barcelona, (Spain). Phone: +34-933125844. E-mail: aandres@ub.edu

Abstract

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.

El presente estudio explora la utilidad de la cuantificación diádica de las características grupales para predecir el rendimiento en equipos de trabajo. Tras revisar la literatura relacionada con el estudio de las características de los miembros de un grupo para predecir el rendimiento grupal, se encontraron porcentajes de varianza explicada de entre el 3% y el 18%. Estos estudios han seguido el denominado enfoque individual, fundamentado en la agregación, para resumir las características de los grupos (e. g., media y varianza). El objetivo del presente estudio es poner a prueba si, mediante medidas diádicas se puede incrementar el porcentaje de predicción del rendimiento grupal. La base de las medidas diádicas son datos obtenidos a partir de pares de individuos interdependientes. Concretamente, en la presente investigación se pretende desarrollar un nuevo índice diádico para medir disimilitud en personalidad en grupos y verificar si las medidas diádicas mejoran la predicción del rendimiento grupal en comparación con las predicciones obtenidas mediante índices basados en la perspectiva individual. Mediante regresión lineal fue explicado el 49.5% de la variabilidad en el rendimiento grupal utilizando como predictoras las medidas tomadas mediante los índices diádicos de antisimetría y disimilitud en personalidad. Estos resultados apoyan la utilidad de la perspectiva diádica para predecir el rendimiento grupal.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2011

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