In no uncertain terms: Group cohesion did not affect exploration and group decision making under low uncertainty

Group decision making under uncertainty often requires groups to balance exploration of their environment with exploitation of the seemingly best option. In order to succeed at this collective induction, groups need to merge the knowledge of all group members and combine goal-oriented and social motivations (i.e., group cohesion). This paper presents three studies that investigate whether more cohesive groups perform worse at collective induction tasks as they spend less time exploring possible options. Study 1 simulates group decision making with the ε-greedy algorithm in order to identify suitable manipulations of group cohesion and investigate how differing exploration lengths can affect outcomes of group decisions. Study 2 (N = 108, 18 groups á 6 participants) used an experimental manipulation of group cohesion in a simple card choice task to investigate how group cohesion might affect group decision making when only limited social information is available. Study 3 (N = 96, 16 groups á 6 participants) experimentally manipulated group cohesion and used the HoneyComb paradigm, a movement-based group experiment platform, to investigate which group processes would emerge during decision making and how these processes would affect the relationships between group cohesion, exploration length, and group decision making. Study 1 found that multiplicative cohesion rewards have detrimental effects on group decision making, while additive group rewards could ameliorate negative effects of the cohesion reward, especially when reported separately from task rewards. Additionally, exploration length was found to profoundly affect decision quality. Studies 2 and 3 showed that groups could identify the best reward option successfully, regardless of group cohesion manipulation. This effect is interpreted as a ceiling effect as the decision task was likely too easy to solve. Study 3 identified that spatial group cohesion on the playing field correlated with self-reported entitativity and leader-/followership emerged spontaneously in most groups and correlated with self-reported perceptions of leader-/followership in the game. We discuss advantages of simulation studies, possible adaptations to the ε-greedy algorithm, and methodological aspects of measuring behavioral group cohesion and leadership to inform empirical studies investigating group decision making under uncertainty.

[1]  Paul J. Pritz,et al.  Modeling of human group coordination , 2022, Physical Review Research.

[2]  I. Couzin,et al.  The geometry of decision-making in individuals and collectives , 2021, Proceedings of the National Academy of Sciences.

[3]  M. Boos,et al.  How collective reward structure impedes group decision making: An experimental study using the HoneyComb paradigm , 2021, PloS one.

[4]  F. von Ameln Führen und Entscheiden unter Unsicherheit , 2021, Gruppe. Interaktion. Organisation. Zeitschrift für Angewandte Organisationspsychologie (GIO).

[5]  Diana Lee,et al.  Inclined but less skilled? Disentangling extraversion, communication skill, and leadership emergence. , 2021, The Journal of applied psychology.

[6]  C. Summerfield,et al.  Human optional stopping in a heteroscedastic world. , 2021, Psychological review.

[7]  F. Fenton,et al.  Unimapper: An Online Interactive Analyzer/Visualizer of Optical Mapping Experimental Data , 2021, 2021 Computing in Cardiology (CinC).

[8]  J. Hüffmeier,et al.  Together, everyone achieves more-or, less? An interdisciplinary meta-analysis on effort gains and losses in teams. , 2021, Psychological bulletin.

[9]  W. Warren,et al.  Nonverbal leadership emergence in walking groups , 2020, Scientific Reports.

[10]  Nicholas P. Aramovich,et al.  The relative importance of participative versus decisive behavior in predicting stakeholders' perceptions of leader effectiveness , 2020 .

[11]  Anita L. Blanchard,et al.  Developing an entitativity measure and distinguishing it from antecedents and outcomes within online and face-to-face groups , 2020 .

[12]  Gelmar García-Vidal,et al.  The impact of self-confidence, creativity and vision on leadership performance: Perceptions at Ecuadorian SMEs owner/managers , 2019, Serbian Journal of Management.

[13]  Margarete Boos,et al.  The HoneyComb Paradigm for Research on Collective Human Behavior. , 2019, Journal of visualized experiments : JoVE.

[14]  Kyanoush Seyed Yahosseini,et al.  Social information can undermine individual performance in exploration-exploitation tasks , 2018, CogSci.

[15]  Saša Baškarada,et al.  Balancing transactional and transformational leadership , 2017 .

[16]  Peter J. Richerson,et al.  Collective action and the evolution of social norm internalization , 2017, Proceedings of the National Academy of Sciences.

[17]  M. Amin Rahimian,et al.  Bayesian Decision Making in Groups is Hard , 2017, Oper. Res..

[18]  Dirk Helbing,et al.  Crowd behaviour during high-stress evacuations in an immersive virtual environment , 2016, Journal of The Royal Society Interface.

[19]  James A Grand,et al.  The dynamics of team cognition: A process-oriented theory of knowledge emergence in teams. , 2016, The Journal of applied psychology.

[20]  Robert Boyd,et al.  Partial connectivity increases cultural accumulation within groups , 2016, Proceedings of the National Academy of Sciences.

[21]  R. Boyd,et al.  The foundations of the human cultural niche , 2015, Nature Communications.

[22]  I. Couzin,et al.  Shared decision-making drives collective movement in wild baboons , 2015, Science.

[23]  Iain D Couzin,et al.  Potential Leaders Trade Off Goal-Oriented and Socially Oriented Behavior in Mobile Animal Groups , 2015, The American Naturalist.

[24]  Margarete Boos,et al.  Leadership in Moving Human Groups , 2014, PLoS Comput. Biol..

[25]  M. Vugt,et al.  The evolutionary psychology of leadership , 2014 .

[26]  Robert L. Goldstone,et al.  Social Learning Strategies in Networked Groups , 2013, Cogn. Sci..

[27]  Margarete Boos,et al.  Spontaneous flocking in human groups , 2013, Behavioural Processes.

[28]  Steve W. J. Kozlowski,et al.  The Dynamics of Emergence: Cognition and Cohesion in Work Teams , 2012 .

[29]  Amy R. Bland,et al.  Different Varieties of Uncertainty in Human Decision-Making , 2012, Front. Neurosci..

[30]  Larissa Conradt,et al.  Models in animal collective decision-making: information uncertainty and conflicting preferences , 2012, Interface Focus.

[31]  D. Knippenberg,et al.  Group leadership and shared task representations in decision making groups , 2012 .

[32]  Winter A. Mason,et al.  Collaborative learning in networks , 2011, Proceedings of the National Academy of Sciences.

[33]  Alex Mesoudi,et al.  An experimental comparison of human social learning strategies: payoff-biased social learning is adaptive but underused , 2011 .

[34]  J. Henrich,et al.  The cultural niche: Why social learning is essential for human adaptation , 2011, Proceedings of the National Academy of Sciences.

[35]  Andrew J. King,et al.  Where Next? Group Coordination and Collective Decision Making by Primates , 2011, International Journal of Primatology.

[36]  P. R. Laughlin Social choice theory, social decision scheme theory, and group decision-making , 2011 .

[37]  Christina Fang,et al.  Balancing Exploration and Exploitation through Structural Design: The Isolation of Subgroups and Organization Learning , 2008 .

[38]  T. Lillicrap,et al.  Why Copy Others? Insights from the Social Learning Strategies Tournament , 2010, Science.

[39]  Dirk Helbing,et al.  Collective Information Processing and Pattern Formation in Swarms, Flocks, and Crowds , 2009, Top. Cogn. Sci..

[40]  Martin L. Martens,et al.  Sticking it All Together: A Critical Assessment of the Group Cohesion–Performance Literature , 2009 .

[41]  Larissa Conradt,et al.  Conflicts of interest and the evolution of decision sharing , 2009, Philosophical Transactions of the Royal Society B: Biological Sciences.

[42]  David Lusseau,et al.  The emergence of unshared consensus decisions in bottlenose dolphins , 2009, Behavioral Ecology and Sociobiology.

[43]  I. Couzin Collective cognition in animal groups , 2009, Trends in Cognitive Sciences.

[44]  I. Couzin,et al.  “Leading According to Need” in Self‐Organizing Groups , 2009, The American Naturalist.

[45]  Timothy D. Hanks,et al.  Probabilistic Population Codes for Bayesian Decision Making , 2008, Neuron.

[46]  Matthew J. Salganik,et al.  Leading the Herd Astray: An Experimental Study of Self-fulfilling Prophecies in an Artificial Cultural Market , 2008, Social psychology quarterly.

[47]  Robert L. Goldstone,et al.  Propagation of innovations in networked groups. , 2008, Journal of experimental psychology. General.

[48]  M. Shadlen,et al.  Decision-making with multiple alternatives , 2008, Nature Neuroscience.

[49]  Angela J. Yu,et al.  Should I stay or should I go? How the human brain manages the trade-off between exploitation and exploration , 2007, Philosophical Transactions of the Royal Society B: Biological Sciences.

[50]  A. Roets,et al.  Separating Ability From Need: Clarifying the Dimensional Structure of the Need for Closure Scale , 2007, Personality & social psychology bulletin.

[51]  Beatrice Rammstedt,et al.  Kurzversion des Big Five Inventory (BFI-K): , 2005 .

[52]  L. Conradt,et al.  Consensus decision making in animals. , 2005, Trends in ecology & evolution.

[53]  Andrew M Simons,et al.  Many wrongs: the advantage of group navigation. , 2004, Trends in ecology & evolution.

[54]  G. Stasser,et al.  Hidden Profiles: A Brief History , 2003 .

[55]  T. Valone,et al.  Potential disadvantages of using socially acquired information. , 2002, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[56]  I. Couzin,et al.  Collective memory and spatial sorting in animal groups. , 2002, Journal of theoretical biology.

[57]  Dirk Helbing,et al.  Simulating dynamical features of escape panic , 2000, Nature.

[58]  M. Hogg Subjective Uncertainty Reduction through Self-categorization: A Motivational Theory of Social Identity Processes , 2000 .

[59]  P. R. Laughlin,et al.  Collective Induction: Twelve Postulates. , 1999, Organizational behavior and human decision processes.

[60]  M. Tomasello The Human Adaptation for Culture , 1999 .

[61]  Lowell Gaertner,et al.  Perceived ingroup entitativity and intergroup bias: an interconnection of self and others , 1998 .

[62]  S. Goyal,et al.  Learning from neighbours , 1998 .

[63]  Marc D. Street Groupthink , 1997 .

[64]  A. Damasio,et al.  Insensitivity to future consequences following damage to human prefrontal cortex , 1994, Cognition.

[65]  J. March Exploration and exploitation in organizational learning , 1991, STUDI ORGANIZZATIVI.

[66]  R L Helmreich,et al.  Negative and positive components of psychological masculinity and femininity and their relationships to self-reports of neurotic and acting out behaviors. , 1979, Journal of personality and social psychology.

[67]  J. Hahn Victims Of Groupthink A Psychological Study Of Foreign Policy Decisions And Fiascoes , 2016 .

[68]  Ben R. Newell,et al.  Unpacking the Exploration–Exploitation Tradeoff: A Synthesis of Human and Animal Literatures , 2015 .

[69]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[70]  Beatrice Rammstedt,et al.  Eine Single-Item-Skala zur Erfassung von Risikobereitschaf: Die Kurzskala Risikobereitschaft-1 (R-1) , 2014 .

[71]  T. Kameda,et al.  Evolution and Groups , 2013 .

[72]  A. Eliyana,et al.  THE INFLUENCE OF LEADER SELF-MASTERY, LEADER PERSONALITY AND LEADER PERSONAL BRANDING ON ACHIEVEMENT MOTIVATION AND LEADER CANDIDATE PERFORMANCE: A STUDY AT P.T. MANGIUM ANUGERAH LESTARI, KOTABARU REGENCY, SOUTH KALIMANTAN , 2013 .

[73]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[74]  I. Couzin,et al.  Self-Organization and Collective Behavior in Vertebrates , 2003 .

[75]  P. R. Laughlin,et al.  A Theory of Collective Induction , 1995 .