Ranking Features on Psychological Dynamics of Cooperative Team Work through Bayesian Networks

The aim of this study is to rank some features that characterize the psychological dynamics of cooperative team work in order to determine priorities for interventions and formation: leading positive feedback, cooperative manager and collaborative manager features. From a dataset of 20 cooperative sport teams (403 soccer players), the characteristics of the prototypical sports teams are studied using an average Bayesian network (BN) and two special types of BNs, the Bayesian classifiers: naive Bayes (NB) and tree augmented naive Bayes (TAN). BNs are selected as they are able to produce probability estimates rather than predictions. BN results show that the antecessors (the “top” features ranked) are the team members’ expectations and their attraction to the social aspects of the task. The main node is formed by the cooperative behaviors, the consequences ranked at the BN bottom (ratified by the TAN trees and the instantiations made), the roles assigned to the members and their survival inside the same team. These results should help managers to determine contents and priorities when they have to face team-building actions.

[1]  Nir Friedman,et al.  Probabilistic Graphical Models - Principles and Techniques , 2009 .

[2]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[3]  Nir Friedman,et al.  Bayesian Network Classifiers , 1997, Machine Learning.

[4]  Frank van Harmelen,et al.  Handbook of Knowledge Representation , 2008, Handbook of Knowledge Representation.

[5]  Shigeo Abe DrEng Pattern Classification , 2001, Springer London.

[6]  Richard E. Neapolitan,et al.  Learning Bayesian networks , 2007, KDD '07.

[7]  F. Atienza,et al.  Análisis psicométrico de la versión española de la escala de liderazgo para el deporte de Chelladurai y Saleh en la versión entrenadores , 1994 .

[8]  C. Glymour The Mind's Arrows: Bayes Nets and Graphical Causal Models in Psychology , 2000 .

[9]  Matthew J. Smith,et al.  Measurement of Transformational Leadership and its Relationship with Team Cohesion and Performance Level , 2009 .

[10]  David W. Hosmer,et al.  Applied Logistic Regression , 1991 .

[11]  Concha Bielza,et al.  New insights into the classification and nomenclature of cortical GABAergic interneurons , 2013, Nature Reviews Neuroscience.

[12]  Radhakrishnan Nagarajan,et al.  Bayesian Networks in R: with Applications in Systems Biology , 2013 .

[13]  John Stillwell,et al.  Symmetry , 2000, Am. Math. Mon..

[14]  Marek J. Druzdzel,et al.  What Do College Ranking Data Tell Us About Student Retention , 1994 .

[15]  Felipe Schneider Costa,et al.  Analysis of Bayesian Classifier accuracy , 2013, J. Comput. Sci..

[16]  Antoni Ligeza,et al.  Bayesian network modeling: A case study of an epidemiologic system analysis of cardiovascular risk , 2016, Comput. Methods Programs Biomed..

[17]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[18]  R. Rico,et al.  Efectividad de los Equipos de Trabajo, una Revisión de la Última Década de Investigación (1999-2009) , 2010 .

[19]  Nicholas D. Myers,et al.  Reciprocal Relationships Between Collective Efficacy and Team Performance in Women's Ice Hockey. , 2004 .

[20]  Kevin T. Kelly,et al.  Discovering Causal Structure. , 1989 .

[21]  A. García-Mas,et al.  Relationships between Cooperation and Goal Orientation among Male Professional and Semi-Professional Team Athletes , 2014, Perceptual and motor skills.

[22]  Adnan Darwiche Bayesian networks , 2010, Commun. ACM.

[23]  D. Beal,et al.  Cohesion and performance in groups: a meta-analytic clarification of construct relations. , 2003, The Journal of applied psychology.

[24]  J. Pearl Causality: Models, Reasoning and Inference , 2000 .

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

[26]  Finn V. Jensen,et al.  Bayesian Networks and Decision Graphs , 2001, Statistics for Engineering and Information Science.

[27]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[28]  Pedro M. Domingos,et al.  On the Optimality of the Simple Bayesian Classifier under Zero-One Loss , 1997, Machine Learning.

[29]  P. Spirtes,et al.  Causation, Prediction, and Search, 2nd Edition , 2001 .

[30]  M. Eys,et al.  Role Ambiguity in Sport Teams , 2003 .

[31]  S. G. Cohen,et al.  What Makes Teams Work: Group Effectiveness Research from the Shop Floor to the Executive Suite , 1997 .

[32]  Nils Lid Hjort,et al.  Model Selection and Model Averaging , 2001 .

[33]  Marina Jirotka,et al.  On the social organisation of organisations , 1992, Computer Supported Cooperative Work (CSCW).

[34]  David Sloan Wilson,et al.  Generalizing the core design principles for the efficacy of groups , 2013, Journal of Economic Behavior & Organization.

[35]  Ramón Rico,et al.  Efectividad de los Equipos de Trabajo, una Revisión de la Última Década de Investigación (1999-2009) Work Team Effectiveness, a Review of Research over the last Decade (1999-2009) , 2010 .

[36]  David Maxwell Chickering,et al.  Learning Bayesian Networks: The Combination of Knowledge and Statistical Data , 1994, Machine Learning.

[37]  Gregory F. Cooper,et al.  A Bayesian Method for the Induction of Probabilistic Networks from Data , 1992 .

[38]  Janis A. Cannon-Bowers,et al.  Teamwork competencies: the interaction of team member knowledge, skills and attitude , 1997 .

[39]  F. Ponseti,et al.  Team performance and collective efficacy in the dynamic psychology of competitive team: a Bayesian network analysis. , 2015, Human movement science.

[40]  อนิรุธ สืบสิงห์,et al.  Data Mining Practical Machine Learning Tools and Techniques , 2014 .

[41]  David Heckerman,et al.  Bayesian Networks for Data Mining , 2004, Data Mining and Knowledge Discovery.

[42]  Ana Cristina Costa,et al.  Work team trust and effectiveness , 2003 .

[43]  Jean-Philippe Heuzé,et al.  Relationships between cohesion, collective efficacy and performance in professional basketball teams: An examination of mediating effects , 2006, Journal of sports sciences.

[44]  Cory J. Butz,et al.  A simple graphical approach for understanding probabilistic inference in Bayesian networks , 2009, Inf. Sci..

[45]  Marco Scutari,et al.  Learning Bayesian Networks with the bnlearn R Package , 2009, 0908.3817.

[46]  Kevin B. Korb,et al.  Bayesian Artificial Intelligence , 2004, Computer science and data analysis series.

[47]  F. Ponseti,et al.  A Bayesian network to discover relationships between negative features in sport: a case study of teen players , 2014 .

[48]  Concha Bielza,et al.  Discrete Bayesian Network Classifiers , 2014, ACM Comput. Surv..

[49]  E. Ortega,et al.  Cohesión y cooperación en equipos deportivos , 2011 .

[50]  Pilar Fuster-Parra,et al.  Cooperative Team Work Analysis and Modeling: A Bayesian Network Approach , 2015, CDVE.

[51]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[52]  Adnan Darwiche,et al.  Bayesian Networks , 2008, Handbook of Knowledge Representation.

[53]  David G. Stork,et al.  Pattern Classification , 1973 .

[54]  Tammy L. Rapp,et al.  Team Effectiveness 1997-2007: A Review of Recent Advancements and a Glimpse Into the Future , 2008 .

[55]  A. Carrón,et al.  Team cohesion and team success in sport , 2002, Journal of sports sciences.