Modeling Teams: A General Systems Theory Approach Advisor: Prof. Sara McComb (OM) Committee Members: Prof. Ronald Karren (OB) Prof. Soren Bisgaard (OM) Prof. Abhijit Deshmukh (MIE)

Research Question Study Design Results and Contributions Dissertation Process Challenges

Dissertation Stage Research Question Theoretical Basis Dissertation completed Research Question Apply General Systems Theory to team modeling Theoretical Basis Team Behavioral Research Simulation Studies General Systems Theory First, a framework for GST application to team model development will be developed and presented. This framework will be based on the theoretical achievements of General Systems Theory. It will contribute to team model development research because GST introduces time and complexity in the models. The framework will facilitate the development of comprehensive, complex and dynamic team behavior models. Second, a team behavior model will be constructed, using the framework guidelines and based on team behavior research. This model will illustrate how the GST and team behavior can be merged in practice. Third, the model development framework will be applied. The coefficients in the GST based team model, describing the relationships will be assessed through meta-analysis. This meta-analysis is intended to summarize the current empirical results and thus present a model that is representative of the state of the art of the field. Fourth, to verify that the framework produces useful models, an experiment showing the dynamics of team behavior will be designed and conducted. The relationships of interest will be obtained and GST experimental team behavior model constructed. The second objective of the doctoral research presented here is to introduce the analyses of model behavior specific to GST. These analyses show the equifinality, stability and behavior at and near equilibrium and provide valuable information about the dynamics of team behavior. First, their theoretical foundation is presented and their applicability and contribution to team behavior research discussed. Second, the theoretically derived model with an empirically obtained one will be compared. The meta-analytic and the empirically derived models with GST tools and the results obtained will be compared and discussed.

Study Design Data Collected via Behavioral Simulation Sample – 72 three person teams, face-to-face and computer-mediated condition (2 X 2 design). Task – develop a work-force schedule. Procedure – two sessions 45 minutes each. Specifically, the experimental task is to develop a work-force schedule. This is an assignment optimization problem, characterized by the need to pair items in one group with items in another group in a one-to-one matching. For example, a set of workers needs to be paired with available workdays. Thus, each worker is assigned to work on a particular day in one or more time slots. The experiment will be conducted with 3 person teams of undergraduate students recruited from management classes held during Fall – Spring 2003. The sample size will be approximately 60 – 70 teams, totaling about 200 participants (Cohen and Cohen (1983). They yielded 53 teams. The experiment is expected to last about 90 minutes each session. First the experimenter will introduce herself and the task, then she will assign each team member to be the enforcer of one decision rule. Next, the teams will have 45 minutes to complete the schedule. The experimenter will collect the schedules and distribute the post-test surveys. The experiment will finish after the surveys are completed. The experiment will be tape recorded and video-taped.

Results Regression Analyses Model Construction Model Simulations A system is deterministic when the relationships within the system do not depend on chance. Deterministic systems are fully specified and do not exhibit any random behavior. In stochastic systems, the relationships in the system depend on chance and the behavior exhibited is random. In this work I assume that the system and subsequent team behavior is deterministic. This assumption allows the resulting model to be verified with conventional statistics. The definition and the mathematical representation of a system make it clear that every system can be modeled as a collection of subsystems (Hall and Fagen, 1968). Each subsystem can be defined as a system on its own, following the framework described above. I strive to develop an abstract model of team behavior, encompassing all team processes commonly discussed in literature. To achieve this and at the same time avoid an overly complex model, I do not consider any subsystems here.

Contributions Theoretical: Social system modeling GST applicable to social systems Current empirical research can be organized following the framework developed Hypothesized model can be estimated via multiple regression Simulated models show dynamics GST analyses provide complementary information Practical: Team Behavior Importance of learning and history Differences between face-to-face and computer-mediated teams A system is deterministic when the relationships within the system do not depend on chance. Deterministic systems are fully specified and do not exhibit any random behavior. In stochastic systems, the relationships in the system depend on chance and the behavior exhibited is random. In this work I assume that the system and subsequent team behavior is deterministic. This assumption allows the resulting model to be verified with conventional statistics. The definition and the mathematical representation of a system make it clear that every system can be modeled as a collection of subsystems (Hall and Fagen, 1968). Each subsystem can be defined as a system on its own, following the framework described above. I strive to develop an abstract model of team behavior, encompassing all team processes commonly discussed in literature. To achieve this and at the same time avoid an overly complex model, I do not consider any subsystems here.

Dissertation Process Proposal started – February 2003. Proposal defended (6 chapters written and approved) – August 2003. Behavioral simulation pretested – October - November 2003. Behavioral simulation conducted – February – April 2004. Data analyzed – July 2004. Simulations completed – September 2004. First draft of Results and Discussion ready – mid December 2004. Second draft of Results and Discussion ready – end of January 2005. Defense scheduled – March 4th 2005. Defended – March 31st 2005. Dissertation submitted to Graduate School – August 2005.

Challenges Time Management Working with the dissertation committee All steps took longer than expected. Writing. Formatting. Empirical data collection. Allow enough time to notify participants. Constantly remind participants to show. Keep track of all data collected – tapes, recordings, questionnaires. Collect all data that you can, even if it looks useless at the time. Allow cushion time for unforeseen problems. Working with the dissertation committee Faculty are busy. Don’t expect immediate reply. Don’t expect them to remember intricate details from your statistical analysis two weeks after the meeting.

Things That I did not do .. and regret it Develop support system Fellow students to talk for work. Friends to complain. Family/ Significant other for moral support. Design relaxation technique Devise alternative plan – what to do if the results are insignificant?