Collective Choice, Collaboration, and Communication

Verbal information exchange enhances collective performance through increasing group identification

Information exchange is a key factor in the attainment of collective outcomes and the navigation of social life. In the current study, we investigated whether and how information exchange enhanced collective performance by combining behavioral and neuroimaging approaches from the perspective of multiparticipant neuroscience. To evaluate collective performance, we measured the collaborative problem-solving abilities of triads working on a murder mystery case. We first found that verbal information exchange significantly enhanced collective performance compared to nonverbal exchange. Moreover, both group sharing and group discussion positively contributed to this effect, with group discussion being more essential. Importantly, group identification mediated the positive effect of verbal information exchange on collective performance. This mediation was supported by higher interactive frequency and enhanced within-group neural synchronization (GNS) in the dorsolateral prefrontal cortex (DLPFC). Taken together, we provided a multiparticipant theoretical model to explain how verbal information exchange enhanced collective performance. Our findings deepen the insight into the workings of group decision-making.

Collaborate as a flock in the organization: how selection and synthesis influence knowledge convergence within a complex adaptive system

Purpose

This study aims to investigate how two collaborative methods – selection and synthesis – influence knowledge convergence when people articulate a new strategic direction driving transformation within the organization.

Design/methodology/approach

The study is based on a longitudinal field experiment developed in four organizations involving 82 employees over a three-month process. Inspired by dynamics governing flocks as complex adaptive systems, selection and synthesis have been separately used in two sets of companies. Primary and secondary data have been largely collected and analyzed throughout the whole process.

Findings

This study describes how the two alternative methods differently influenced two kinds of knowledge convergence. While selection triggers a general and static knowledge convergence and the propagation of individual knowledge over time, synthesis fosters a local and dynamic knowledge convergence where individuals tend to propagate knowledge generated collectively.

Research limitations/implications

This research offers insights into understanding the influence of alternative collaborative methods on the creation and propagation of knowledge when people are converging toward a new strategic direction. From a theoretical perspective, it contributes to complex adaptive system theory, highlighting the role of knowledge convergence and emergence through collaboration.

Practical implications

This research offers insights to managers who deal with the complexity of the engagement of different stakeholders during collaborative processes, offering some actionable takeaways to foster knowledge convergence by alternatively employing selection and synthesis.

Originality/value

This paper contributes to the management and social information processing literature emphasizing the role of knowledge convergence emerging from the complex interactions among multiple stakeholders.

Pooling decisions decreases variation in response bias and accuracy

Decision makers in contexts as diverse as medical, judicial, and political decision making are known to differ substantially in response bias and accuracy, and these differences are a major factor undermining the reliability and fairness of the respective decision systems. Using theoretical modeling and empirical testing across five domains, we show that collective systems based on pooling decisions robustly overcome this important but as of now unresolved problem of experts' heterogeneity. In breast and skin cancer diagnostics and fingerprint analysis, we find that pooling the decisions of five experts reduces the variation in sensitivity among decision makers by 52%, 54%, and 41%, respectively. Similar reductions are achieved for specificity and response bias, and in other domains. Thus, although outcomes in individual decision systems are highly variable and at the mercy of individual decision makers, collective systems based on pooling decrease this variation, thereby promoting reliability, fairness, and possibly even trust.

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Professional decision makers typically differ in their response bias and accuracy

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Such differences undermine the reliability and fairness of decision systems

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Pooling decisions reduces such variation in response bias and accuracy

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This occurred in cancer diagnostics, fingerprint analysis, and forecasting

[Importance of the COVID-19 pandemic for public health and group psychological aspects-Part 2 of a (preliminary) review]

Based upon the findings related to the impact of the coronavirus disease 2019 (COVID-19) pandemic on human living conditions and psychological health, in the first part of this review the authors discuss the consequences of the pandemic for public health. It is surprising to see that related to public health but also psychological factors and sequelae of the pandemic, a broad knowledge was already available based upon former pandemics and disasters long before the outbreak of COVID-19. This knowledge has been used very sparsely, if at all, for health political decisions. In view of the social significance of the pandemic and its social impact, findings from group psychology and group dynamics seem to be specifically important for a better understanding of behavior within the population as well as the conceptualization of public health interventions. An increase in psychological disorders was described related to the pandemic. For the treatment of these disorders, a range of psychotherapeutic approaches including evidence-based group psychotherapy are available. Whereas the use of telemedical and digital techniques is increasingly more common within individual psychotherapy, many questions are still open related to online group treatment.

Group decisions based on confidence weighted majority voting

Background

It has repeatedly been reported that, when making decisions under uncertainty, groups outperform individuals. Real groups are often replaced by simulated groups: Instead of performing an actual group discussion, individual responses are aggregated by a numerical computation. While studies have typically used unweighted majority voting (MV) for this aggregation, the theoretically optimal method is confidence weighted majority voting (CWMV)—if independent and accurate confidence ratings from the individual group members are available. To determine which simulations (MV vs. CWMV) reflect real group processes better, we applied formal cognitive modeling and compared simulated group responses to real group responses.

Results

Simulated group decisions based on CWMV matched the accuracy of real group decisions, while simulated group decisions based on MV showed lower accuracy. CWMV predicted the confidence that groups put into their group decisions well. However, real groups treated individual votes to some extent more equally weighted than suggested by CWMV. Additionally, real groups tend to put lower confidence into their decisions compared to CWMV simulations.

Conclusion

Our results highlight the importance of taking individual confidences into account when simulating group decisions: We found that real groups can aggregate individual confidences in a way that matches statistical aggregations given by CWMV to some extent. This implies that research using simulated group decisions should use CWMV instead of MV as a benchmark to compare real groups to.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41235-021-00279-0.