The Experts below are selected from a list of 257778 Experts worldwide ranked by ideXlab platform
Paul V Martorana - One of the best experts on this subject based on the ideXlab platform.
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the impact of chief executive officer personality on top management team Dynamics one mechanism by which leadership affects organizational performance
Journal of Applied Psychology, 2003Co-Authors: Randall S Peterson, Brent D Smith, Paul V Martorana, Pamela D OwensAbstract:This article explores 1 mechanism by which leader personality affects organizational performance. The authors hypothesized and tested the effects of leader personality on the Group Dynamics of the top management team (TMT) and of TMT Dynamics on organizational performance. To test their hypotheses, the authors used the Group Dynamics q-sort method, which is designed to permit rigorous, quantitative comparisons of data derived from qualitative sources. Results from independent observations of chief executive officer (CEO) personality and TMT Dynamics for 17 CEOs supported the authors’ hypothesized relationships both between CEO personality and TMT Group Dynamics and between TMT Dynamics and organizational performance.
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Group Dynamics in top management teams Groupthink vigilance and alternative models of organizational failure and success
Organizational Behavior and Human Decision Processes, 1998Co-Authors: Randall S Peterson, Pamela D Owens, Philip E Tetlock, Elliott T Fan, Paul V MartoranaAbstract:This study explored the heuristic value of Janis' (1982) Groupthink and vigilant decision making models as explanations of failure and success in top management team decision making using the Organizational Group Dynamics Q-sort (GDQ). Top management teams of seven Fortune 500 companies were examined at two historical junctures-one when the team was successful (defined as satisfying strategic constituencies) and one when the team was unsuccessful. Results strongly supported the notion that a Group' decision making process is systematically related to the outcomes experienced by the team. Ideal-type Q-sorts organized around Janis' analysis of Groupthink and vigilance were substantially correlated with Q-sorts of failing and successful Groups, respectively. The fit was, however, far from perfect. Ideal-type Q-sorts derived from other frameworks correlated better with the failure-success classification than did the Janis-derived ideal types. Successful Groups showed some indicators of Groupthink (e.g., risk-taking, cohesion, and strong, opinionated leaders), whereas unsuccessful Groups showed signs of vigilance (e.g., internal debate to the point of factionalism). The results illustrate the usefulness of the GDQ for developing and empirically testing theory in organizational behavior from historical cases. Copyright 1998 Academic Press.
Mark R Beauchamp - One of the best experts on this subject based on the ideXlab platform.
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Group Dynamics in exercise and sport psychology
2014Co-Authors: Mark R Beauchamp, Mark A EysAbstract:Preface Foreword Part I: The Self in Groups Chapter 1: Emotional Intelligence - A Framework for Examining Emotions in Sport and Exercise Groups Chapter 2: 'Into The Mix': Personality Processes and Group Dynamics in Sport Teams Chapter 3: A Social Identity Perspective on Group Processes in Sport and Exercise Part II: Leadership in Groups Chapter 4: Transformational Leadership in Sport Chapter 5: Coach-Athlete Relationships and Attachment Styles Within Sport Teams Chapter 6: Proxy Agency and Other-Efficacy in Physical Activity Chapter 7: Athlete Leadership in Sport Part III: Group Environment Chapter 8: Role Perceptions in Sport Groups Chapter 9: Group Cohesion in Sport and Exercise Settings Chapter 10: Group Integration Interventions in Exercise: Theory, Practice, and Future Directions Chapter 11: Efficacy of a Group-Mediated Cognitive Behavioral Intervention: A Decade of Physical Activity Research Chapter 12: The Family as a Context for Physical Activity Promotion Chapter 13: Coping, Social Support, and Emotion Regulation in Teams Chapter 14: Coordination in Sports Teams. Part IV: Motivation in Groups Chapter 15: Self-Determined Motivation in Sport and Exercise Groups Chapter 16: Group Functioning Through Optimal Achievement Goals Chapter 17: Collective Efficacy Beliefs and Sport Part V: Socio-environmental Issues in Groups Chapter 18: Cultural Diversity Within Group Dynamics in Sport Chapter 19: Gendered Social Dynamics in Sport
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into the mix personality processes and Group Dynamics in sport teams
2014Co-Authors: Mark R Beauchamp, Ben Jackson, David LavalleeAbstract:Preface Foreword Part I: The Self in Groups Chapter 1: Emotional Intelligence - A Framework for Examining Emotions in Sport and Exercise Groups Chapter 2: 'Into The Mix': Personality Processes and Group Dynamics in Sport Teams Chapter 3: A Social Identity Perspective on Group Processes in Sport and Exercise Part II: Leadership in Groups Chapter 4: Transformational Leadership in Sport Chapter 5: Coach-Athlete Relationships and Attachment Styles Within Sport Teams Chapter 6: Proxy Agency and Other-Efficacy in Physical Activity Chapter 7: Athlete Leadership in Sport Part III: Group Environment Chapter 8: Role Perceptions in Sport Groups Chapter 9: Group Cohesion in Sport and Exercise Settings Chapter 10: Group Integration Interventions in Exercise: Theory, Practice, and Future Directions Chapter 11: Efficacy of a Group-Mediated Cognitive Behavioral Intervention: A Decade of Physical Activity Research Chapter 12: The Family as a Context for Physical Activity Promotion Chapter 13: Coping, Social Support, and Emotion Regulation in Teams Chapter 14: Coordination in Sports Teams. Part IV: Motivation in Groups Chapter 15: Self-Determined Motivation in Sport and Exercise Groups Chapter 16: Group Functioning Through Optimal Achievement Goals Chapter 17: Collective Efficacy Beliefs and Sport Part V: Socio-environmental Issues in Groups Chapter 18: Cultural Diversity Within Group Dynamics in Sport Chapter 19: Gendered Social Dynamics in Sport
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how dynamic are exercise Group Dynamics examining changes in cohesion within class based exercise programs
Health Psychology, 2013Co-Authors: William L Dunlop, Carl F Falk, Mark R BeauchampAbstract:Objective: Within exercise class settings, Group cohesion has consistently been found to predict adherence behaviors, and has been identified as a salient target for intervention-based initiatives. Drawing upon theorizing from the field of Group Dynamics, exercise class cohesion is often conceptualized as a dynamic construct that requires several classes to form and once it is formed, continues to change over time. Despite the salience of this “dynamic” contention for informing physical activity interventions, this theorizing has yet to be empirically tested. Method: In this study a multilevel modeling framework was used to examine changes in exercise class cohesion over time. Exercisers (N 395) completed measures of cohesion following the second, fifth, and eighth classes of their respective programs (N 46). Results: Mean levels of social cohesion changed significantly over time whereas mean levels of task cohesion did not. These patterns were largely consistent across persons and Groups. Conclusions: These findings suggest that within Group-based exercise programs social and task cohesion possesses different levels of dynamism, and that this dynamism (or lack thereof) might have important implications for future research and interventions involving physical activity Groups.
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Group Dynamics in exercise and sport psychology contemporary themes
2007Co-Authors: Mark R Beauchamp, Mark A EysAbstract:Part 1: The Self in Groups 1. Emotional Intelligence - A Framework for Examining Emotions in Sport and Exercise Groups 2. Personality Processes and Intra-Group Dynamics in Sport Teams Part 2: Leadership in Groups 3. Transformational Leadership and Sports Psychology 4. Coach-Athlete Relationships Ignite Sense of Groupness 5. Proxy Agency in Physical Activity Part 3: Group Environment 6. Role Perceptions in Sport Groups 7. Group Cohesion in Sport and Exercise: Past, Present, and Future 8. Group Integration Interventions in Exercise: Theory, Practice, and Future Directions 9. Gendered Social Dynamics in Sport Part 4: Motivation in Groups 10. Self-Determined Motivation in Sport and Exercise Groups 11. Group Functioning through Optimal Achievement Goals 12. Exploring New Directions in Collective Efficacy and Sport
Randall S Peterson - One of the best experts on this subject based on the ideXlab platform.
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the impact of chief executive officer personality on top management team Dynamics one mechanism by which leadership affects organizational performance
Journal of Applied Psychology, 2003Co-Authors: Randall S Peterson, Brent D Smith, Paul V Martorana, Pamela D OwensAbstract:This article explores 1 mechanism by which leader personality affects organizational performance. The authors hypothesized and tested the effects of leader personality on the Group Dynamics of the top management team (TMT) and of TMT Dynamics on organizational performance. To test their hypotheses, the authors used the Group Dynamics q-sort method, which is designed to permit rigorous, quantitative comparisons of data derived from qualitative sources. Results from independent observations of chief executive officer (CEO) personality and TMT Dynamics for 17 CEOs supported the authors’ hypothesized relationships both between CEO personality and TMT Group Dynamics and between TMT Dynamics and organizational performance.
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Group Dynamics in top management teams Groupthink vigilance and alternative models of organizational failure and success
Organizational Behavior and Human Decision Processes, 1998Co-Authors: Randall S Peterson, Pamela D Owens, Philip E Tetlock, Elliott T Fan, Paul V MartoranaAbstract:This study explored the heuristic value of Janis' (1982) Groupthink and vigilant decision making models as explanations of failure and success in top management team decision making using the Organizational Group Dynamics Q-sort (GDQ). Top management teams of seven Fortune 500 companies were examined at two historical junctures-one when the team was successful (defined as satisfying strategic constituencies) and one when the team was unsuccessful. Results strongly supported the notion that a Group' decision making process is systematically related to the outcomes experienced by the team. Ideal-type Q-sorts organized around Janis' analysis of Groupthink and vigilance were substantially correlated with Q-sorts of failing and successful Groups, respectively. The fit was, however, far from perfect. Ideal-type Q-sorts derived from other frameworks correlated better with the failure-success classification than did the Janis-derived ideal types. Successful Groups showed some indicators of Groupthink (e.g., risk-taking, cohesion, and strong, opinionated leaders), whereas unsuccessful Groups showed signs of vigilance (e.g., internal debate to the point of factionalism). The results illustrate the usefulness of the GDQ for developing and empirically testing theory in organizational behavior from historical cases. Copyright 1998 Academic Press.
Pamela D Owens - One of the best experts on this subject based on the ideXlab platform.
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the impact of chief executive officer personality on top management team Dynamics one mechanism by which leadership affects organizational performance
Journal of Applied Psychology, 2003Co-Authors: Randall S Peterson, Brent D Smith, Paul V Martorana, Pamela D OwensAbstract:This article explores 1 mechanism by which leader personality affects organizational performance. The authors hypothesized and tested the effects of leader personality on the Group Dynamics of the top management team (TMT) and of TMT Dynamics on organizational performance. To test their hypotheses, the authors used the Group Dynamics q-sort method, which is designed to permit rigorous, quantitative comparisons of data derived from qualitative sources. Results from independent observations of chief executive officer (CEO) personality and TMT Dynamics for 17 CEOs supported the authors’ hypothesized relationships both between CEO personality and TMT Group Dynamics and between TMT Dynamics and organizational performance.
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Group Dynamics in top management teams Groupthink vigilance and alternative models of organizational failure and success
Organizational Behavior and Human Decision Processes, 1998Co-Authors: Randall S Peterson, Pamela D Owens, Philip E Tetlock, Elliott T Fan, Paul V MartoranaAbstract:This study explored the heuristic value of Janis' (1982) Groupthink and vigilant decision making models as explanations of failure and success in top management team decision making using the Organizational Group Dynamics Q-sort (GDQ). Top management teams of seven Fortune 500 companies were examined at two historical junctures-one when the team was successful (defined as satisfying strategic constituencies) and one when the team was unsuccessful. Results strongly supported the notion that a Group' decision making process is systematically related to the outcomes experienced by the team. Ideal-type Q-sorts organized around Janis' analysis of Groupthink and vigilance were substantially correlated with Q-sorts of failing and successful Groups, respectively. The fit was, however, far from perfect. Ideal-type Q-sorts derived from other frameworks correlated better with the failure-success classification than did the Janis-derived ideal types. Successful Groups showed some indicators of Groupthink (e.g., risk-taking, cohesion, and strong, opinionated leaders), whereas unsuccessful Groups showed signs of vigilance (e.g., internal debate to the point of factionalism). The results illustrate the usefulness of the GDQ for developing and empirically testing theory in organizational behavior from historical cases. Copyright 1998 Academic Press.
David J Wilman - One of the best experts on this subject based on the ideXlab platform.
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statistical tools for classifying galaxy Group Dynamics
The Astrophysical Journal, 2009Co-Authors: Annie Hou, Laura C Parker, William E Harris, David J WilmanAbstract:The dynamical state of galaxy Groups at intermediate redshifts can provide information about the growth of structure in the universe. We examine three goodness-of-fit tests, the Anderson-Darling (A-D), Kolmogorov, and χ2 tests, in order to determine which statistical tool is best able to distinguish between Groups that are relaxed and those that are dynamically complex. We perform Monte Carlo simulations of these three tests and show that the χ2 test is profoundly unreliable for Groups with fewer than 30 members. Power studies of the Kolmogorov and A-D tests are conducted to test their robustness for various sample sizes. We then apply these tests to a sample of the second Canadian Network for Observational Cosmology Redshift Survey (CNOC2) galaxy Groups and find that the A-D test is far more reliable and powerful at detecting real departures from an underlying Gaussian distribution than the more commonly used χ2 and Kolmogorov tests. We use this statistic to classify a sample of the CNOC2 Groups and find that 34 of 106 Groups are inconsistent with an underlying Gaussian velocity distribution, and thus do not appear relaxed. In addition, we compute velocity dispersion profiles (VDPs) for all Groups with more than 20 members and compare the overall features of the Gaussian and non-Gaussian Groups, finding that the VDPs of the non-Gaussian Groups are distinct from those classified as Gaussian.
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statistical tools for classifying galaxy Group Dynamics
arXiv: Astrophysics of Galaxies, 2009Co-Authors: Annie Hou, Laura C Parker, William E Harris, David J WilmanAbstract:The dynamical state of galaxy Groups at intermediate redshifts can provide information about the growth of structure in the universe. We examine three goodness-of-fit tests, the Anderson--Darling (A-D), Kolmogorov and chi-squared tests, in order to determine which statistical tool is best able to distinguish between Groups that are relaxed and those that are dynamically complex. We perform Monte Carlo simulations of these three tests and show that the chi-squared test is profoundly unreliable for Groups with fewer than 30 members. Power studies of the Kolmogorov and A-D tests are conducted to test their robustness for various sample sizes. We then apply these tests to a sample of the second Canadian Network for Observational Cosmology Redshift Survey (CNOC2) galaxy Groups and find that the A-D test is far more reliable and powerful at detecting real departures from an underlying Gaussian distribution than the more commonly used chi-squared and Kolmogorov tests. We use this statistic to classify a sample of the CNOC2 Groups and find that 34 of 106 Groups are inconsistent with an underlying Gaussian velocity distribution, and thus do not appear relaxed. In addition, we compute velocity dispersion profiles (VDPs) for all Groups with more than 20 members and compare the overall features of the Gaussian and non-Gaussian Groups, finding that the VDPs of the non-Gaussian Groups are distinct from those classified as Gaussian.
