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2 results

  • 10 - Interpersonal Influences in Consumer Psychology

  • from 2 - Consumer Psychology of Groups and Society
  • Edited by Cait Lamberton, Wharton School, University of Pennsylvania, Derek D. Rucker, Kellogg School, Northwestern University, Illinois, Stephen A. Spiller, Anderson School, University of California, Los Angeles
  • Book:
    The Cambridge Handbook of Consumer Psychology
    Published online:
    30 March 2023
    Print publication:
    06 April 2023, pp 273-308

  • Summary

    Consumption is inherently a social activity. Interpersonal influences derive from exposure to others’ communications and actions and can affect the motivations, thoughts, emotions, or behaviors of a given focal consumer. Such influences arise from direct interaction between two or more individuals or from indirect exposure to other individual(s), such as via social media, social norms, or thinking about others. This chapter highlights and integrates the large body of interpersonal influence research from approximately the last five years (published between 2014 and 2021) using an organizing framework built around the customer journey. We also offer thoughts on where we see opportunities for moving interpersonal influences research in new directions.

  • Predicting Team Output Using Indices at Group Level

  • Amara Andrés, Lluís Salafranca, Antonio Solanas
  • Journal:
    The Spanish Journal of Psychology / Volume 14 / Issue 2 / November 2011
    Published online by Cambridge University Press:
    10 January 2013, pp. 773-788

  • 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.