Based on motivated identity construction theory (MICT, Vignoles, 2011), we offer an integrative approach examining the combined roles of six identity motives (self-esteem, distinctiveness, belonging, meaning, continuity and efficacy) instantiated at three different motivational levels (personal, social and collective identity) as predictors of group

Social identification and team performance literatures typically focus on the relationship between individual differences in identification and individual‐level performance. By using a longitudinal multilevel approach, involving 369 members of 45 sports teams across England and Italy, we compared how team‐level and individual‐level variance in social identification together predicted team and individual performance outcomes. As hypothesized, team‐level variance in identification significantly predicted subsequent levels of both perceived and actual team performance in cross‐lagged analyses. Conversely, individual‐level variance in identification did not significantly predict subsequent levels of perceived individual performance. These findings support recent calls for social identity to be considered a multilevel construct and highlight the influence of group‐level social identification on group‐level processes and outcomes, over and above its individual‐level effects.

Introducing monetary fines to decrease an undesired behavior can sometimes have the counterintuitive effect of increasing the prevalence of the behavior being targeted. Such findings raise important social psychological questions in relation to both the way in which financial penalties are framed and the social contexts in which they are administered. In a field experiment (Study 1), we informed participants who had signed up for an experiment that they would be fined if they arrived late. This fine was presented as either compensatory or retributive in nature and as being administered either privately or publicly. We then observed participants' subsequent arrival time. In accordance with our hypotheses, participants' punctuality was only improved (relative to a no-fine control) in response to retributive rather than compensatory fines and when told that fines would be administered publicly rather than privately. In Study 2 we used a scenario method to demonstrate that the greater efficacy of retributively framed fines can be attributed to their presence being less likely to undermine the perceived immorality of transgression than is the case for compensatory fines. We propose a material promotion-moral prevention (MPMP) theory to account for our findings and consider its practical implications for the use of financial disincentives to encourage cooperative behavior through public policy in domains such as climate change.

Although there is a relatively large body of literature which documents evaluations of driver performance with instrument-panel (IP) controls, there does not exist a standard methodology which can be applied to obtain dynamic and objective performance data. Because of this, it is difficult to compare and integrate the findings from different evaluations. To address this problem, the G.M. Systems Engineering Human Factors Department has developed two implementations of a methodology which show promise — the “Video Method” and the “Automated Method.” Both implementations are identical with respect to the experimental tasks performed by the subjects and the types of objective data which can be obtained. The implementations differ, however, with respect to the method by which task completion times and errors are obtained. The Video Method relies upon frame-by-frame video analysis to obtain task completion times, while the Automated Method employs instrumented controls. A computer records driver control inputs, which are later reduced through the use of a custom software package, to obtain task completion times. Because of the differences in data acquisition techniques, both implementations exhibit unique strengths and weaknesses, and differ in their appropriateness for use with certain types of controls.

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