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Team Research: MSU Team Lab

Team Research: MSU Team Lab. An Experimental Approach to Structural Issues in Command and Control Perspective Situation X Person Interaction Situation includes both task structure and task demands Contingency Models Mapping the Structural and Personal Space

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Team Research: MSU Team Lab

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  1. Team Research: MSU Team Lab • An Experimental Approach to Structural Issues in Command and Control • Perspective • Situation X Person Interaction • Situation includes both task structure and task demands • Contingency Models • Mapping the Structural and Personal Space • Horizontal space (Divisional and Functional) • Vertical space (Roles and Power/Status) • Research: Past and Ongoing • Research: Future Directions

  2. Research on Adaptation • Review and discuss 4 studies focused on adaptation in team-based work environments

  3. Adapting to Communication Losses (Lepine, 2003) • Purpose: Examine the factors that allow teams to effectively adapt their routines in response to unforeseen changes in the work environment • Primary contribution: • Extension of individual-level, cognition-focused adaptation research to consider team-level behavior

  4. Member Cognitive Ability Member Achievement Post Change Decision-Making Performance Role Structure Adaptation Member Dependability Member Openness to Exp. Adapting to Communication Losses Theory & Conceptual Model • Teams must be able to deal with unanticipated change and modify their routines (Argote & McGrath, 1993) • Key questions: • What variables predict the extent to which teams adjust their routines in response to unforeseen change? • Do the same factors predict team performance prior to and after unforeseen change?

  5. Adapting to Communication Losses Hypotheses • Hypotheses 2b, 3b, 4b, & 5b: • Member cognitive ability, achievement, and openness to experience positively related to team decision-making performance after change • Member dependability negatively related to team decision-making performance after change Hypothesis 2a, 3a, 4a, & 5a Member Cognitive Ability + Hypothesis 1 + Member Achievement Post Change Decision-Making Performance + Role Structure Adaptation Member Dependability − + Member Openness to Exp. • Hypotheses 2c, 3c, 4c, & 5c: • Role structure adaptation mediates relationship between member cognitive ability, achievement, dependability and openness to experience and team decision-making performance after change

  6. Adapting to Communication Losses Research Design & Methods • TIDE2 decision-making simulation • 73 three-person teams (college juniors and seniors) • Random assignment to teams and roles • Training and practice designed to facilitate development of team routines • Role structure adaptation measured using (a) count method and (b) rated measure

  7. Adapting to Communication Losses Findings & Implications • All hypotheses received empirical support • Suggests that the set of individual differences that predict team performance in a changing situation may be quite distinct from those that predict performance in more routine situations • Implication: Effective team staffing should consider the degree to which the team is likely to experience unexpected change

  8. Adapting to New Adversary Tactics (Porter et al., 2003) • Purpose: Examine the effects of team member personality and legitimacy of need on backing up behaviors in teams • Primary contribution: • Differentiates help in terms of its legitimacy of need • Examines backing up behavior at the team-level • Provides an objective measure of whether help actually ensued

  9. Adapting to New Adversary Tactics Conceptual Model & Hypotheses • Legitimacy of need positively relates to backing up (H1) • Recipient conscientiousness and legitimacy of need interact to predict backing up (H2) • Recipient emotional stability and legitimacy of need interact to predict backing up (H3) • Recipient extraversion and legitimacy of need interact to predict backing up (H4) • Provider conscientiousness and legitimacy of need interact to predict backing up (H5) • Provider emotional stability and legitimacy of need interact to predict backing up (H6) • Provider agreeableness and legitimacy of need interact to predict backing up (H7) Input Team Process • Personality of back up recipient • Personality of back up provider • Legitimacy of need (direct & moderator effect) • Backing up behavior (# of help attacks) Backing Up Behavior: Discretionary provision of resources and task-related effort to another member of one’s team that is intended to help that team member obtain the goals defined by his or her role when it is apparent that the team member is failing to reach those goals

  10. Adapting to New Adversary Tactics Research Design & Methods • DDD decision-making simulation • 71 four-person teams (college juniors and seniors) • Individuals randomly assigned to teams / roles • Teams randomly assigned to high or low-legitimacy condition (based on resource allocation and workload distribution) • Hierarchical regression used to test moderation effects

  11. Adapting to New Adversary Tactics Findings & Implications • Hypotheses 1, 2, 4, and 6 (no support for H3, H5 or H7) • Legitimacy of need predicts backing up behavior • Legitimacy of need interacts with back up provider and recipient personality to predict backing up behavior • Implication: • Personality of the back up provider and recipient can differentially affect the effectiveness of backing up behavior in teams • E.g., showing good discrimination on when to provide back up • Effective team staffing should consider the degree to which team members will experience workload distribution imbalance – and compose the team accordingly • E.g., conscientious and extraverted recipients • E.g., emotionally stable providers

  12. Adapting to New Adversary Technology (Ellis et al., 2003) • Purpose: Examine how project teams learn and how the speed of the learning process can be improved within teams of individuals with no prior history or knowledge of each other’s strengths and weaknesses • Primary contribution: • Expands traditional conceptualization of learning process at the individual level to the team level • Recognizes that team members learn from their own direct experience AND the experience of other team members

  13. Adapting to New Adversary Technology Theory & Conceptual Model • Team Learning • Relatively permanent change in the team’s collective level of knowledge and skill produced by the shared experience of the team members • Accounts for multiple sources of learning in teams • Individual team member’s ability to individually acquire knowledge and skill • Team members’ ability to collectively share information Input Team Process • Member cognitive ability • Workload distribution (even/uneven) • Member agreeableness and openness to experience • Team structure • Pair-based • Functional • Divisional • Team learning

  14. Adapting to New Adversary Technology Hypotheses • Higher levels of general cognitive ability generates higher levels of team learning (H1) • Evenly distributed workloads will engender greater team learning than unevenly distributed workload (H2) • Higher levels of agreeableness will generate lower levels of team learning (H3) • Higher levels of openness to experience will generate higher levels of team learning (H4) • Project teams using pair-based structures will learn more than those structured functionally or divisionally (H5) Input Team Process • Member cognitive ability • Workload distribution (even/uneven) • Member agreeableness and openness to experience • Team structure • Pair-based • Functional • Divisional • Team learning

  15. Adapting to New Adversary Technology Research Design & Methods • DDD decision-making simulation • 109 four-person teams (college juniors and seniors) • Individuals randomly assigned to teams / roles • Teams randomly assigned to paired, functional and divisional structures • Workload distribution manipulated within teams across 2 different 30-minute simulations • Team learning based on the nature of engagement toward a series of Unknown targets • Effective engagement / efficient engagement • Repeated measures regression used to analyze data

  16. Adapting to New Adversary Technology Findings & Implications • Findings support H1, H2, H3, and H5 • Cognitive ability, agreeableness, workload distribution and team structure impact project team learning • Implication: • For project teams operating in contexts that demand learning, effective team staffing should select individuals with high cognitive ability – and not all members should be high in agreeableness • Ensuring even workload distribution and employing team structures where two members have access to the same information helps to eliminate learning barriers

  17. Adapting to Reductions in Size (DeRue et al., 2005) • Purpose: Examine the factors that allow teams to effectively adapt in response to unforeseen reductions in team size • Primary contribution: • Examines the compositional factors and processes that enable teams to effectively adapt to reductions in team size • Explores multiple forms of reductions in team size

  18. Adapting to Reductions in Size Theory & Conceptual Model Post-Change Team Performance Input Mediators • Team structure • Task environment • Individual differences • Form of reduction in team size • Trusting • Structuring • Bonding • Adapting • Learning • Examined 3 forms of reducing team size: • Eliminate hierarchy (eliminate the team leader role) • Integrate hierarchy (leader replaces displaced team member in action role) • Maintain hierarchy (leader position remains; displaced team member not replaced)

  19. Adapting to Reductions in Size Research Design & Methods • DDD decision-making simulation • ~75 five-person teams (college juniors and seniors) • Individuals randomly assigned to teams / roles • Teams randomly assigned to conditions • Data analysis in process

  20. Adapting to Reductions in Size Preliminary Findings • Form of reduction significantly affects team performance • E.g., Leader may not be an adequate substitute for task performing roles • E.g., Losing the team leader has little impact on offensive performance but significantly detracts from team’s ability to monitor the team environment

  21. Adapting to Reductions in SizePreliminary Findings (cont.) • Losing a task performing team member engenders more structuring of roles and responsibilities in the team • Loss of team leader significantly hinders team bonding (potentially more task-focused)

  22. Adapting to Reductions in Size Emerging Implications • Shifting traditional, hierarchical teams to self-managing teams with no formal leader does not always result in superior team performance • Potential short-term bonding loss • Loss of external monitoring function • If forced to downsize, which team members should stay / go? • Key considerations: Task environment? Short-term or long-term perspective?

  23. Structural Asymmetry Research • Review and discuss 4 studies focused on structure in team-based work environments

  24. Purpose • Examine the impact of team structure on team performance and effectiveness by addressing: • the fit of structural conditions to task demands • structural adaptability to changes in task demands • the internal fit of team members to team structures

  25. Dimensions of Structure

  26. Fixed Structures(Hollenbeck et al., 2002) • Structural Contingency Theory • No one best way to structure teams in organizations • Fit of Team Structure to Environment (External Fit) • Team performance will be an interactive effect of the team structure and its task/problem environment • Types of structure • Divisional: People are grouped based on geographic region • Broad Roles • Highly independent • Functional: People are grouped on the basis of the type of the work they perform • Narrow/specialized roles • High levels of interdependence

  27. Fixed Structures(Hollenbeck et al., 2002) • Fit of individuals’ characteristics to the demands placed on team members by different structures • In divisional structures, jobs are complex and have fairly high levels of autonomy • High cognitive ability may be better here • In functional structures, roles are fragmented and there are high levels of interdependence, making coordination very important • Agreeable team members may be important • In misaligned structures/environments, high levels of stress or conflict may occur • Emotional stability is important in dealing with this

  28. Fixed Structures Hypotheses • External Fit: • H1: Functional structures will be superior in predictable environments while divisional structures will be superior in random environments • Internal Fit: • H2: There will be a positive relationship between cognitive ability and individual performance in divisional structures • H3: There will be a positive relationship between agreeableness and individual performance in functional structures • Joint Fit: • H4: In teams with misaligned structures/environments, there will be a positive relationship between emotional stability and individual performance

  29. Fixed Structures Methods • Design: 2 (structure) X 2 (task demand) between subjects • Sample: 80 4-person teams • Task: DDD(MSU) • Measures: • Cognitive Ability (Wonderlic) • Agreeableness & Emot. Stability (NEO-PI-R) • Performance (team & Individual, DDD output)

  30. Fixed Structures Results: External Fit

  31. Fixed Structures Results: Internal and Joint Fit • H2: In aligned divisional structures, cognitive ability was positively related to individual performance (ΔR2 = .04, p < .05) • H3: In aligned functional structures, Individual performance was not related to agreeableness • H4: In misaligned divisional structures, emotional stability was positively related to individual performance (ΔR2 = .03, p < .05) • This relationship was not significant for misaligned functional structures

  32. Structural Asymmetry(Moon et al., in press) • Comparison of 2 types of structural shift • Functional  Divisional • Divisional  Functional • Stimulated by: Need to change; tendency to apply static findings to dynamic situations • Asymmetric Adaptability: structural changes may not be as easy to make in one direction as they are in the other • May be easier to switch from a divisional structure to a functional structure, or vice versa

  33. Structural AsymmetryTheory • Structural shifts may be more or less difficult depending on the types of norms teams develop • Initial norms may carry over to impact future performance • In functional structures, norms are built for cooperation and communication • These norms are not likely to hamper performance when a team switches to a divisional structure • In divisional structures, norms are built for independence • These norms will be detrimental to team performance when a team switches to a functional structure

  34. Structural AsymmetryHypotheses • H1: Functional structures will be superior in predictable environments while divisional structures will be superior in random environments [Replication of Hollenbeck et al. (2002)] • H2: Teams switching from Div. to Fun. structures will perform worse upon switching than teams switching from Fun. to Div. structures • H3: Communication and coordination behaviors mediate the difference in performance between teams engaged in Div. to Fun. and Fun. to Div. structural adaptation • H4: The positive effects of Fun. to Div. structural adaptation will be stronger for teams that are high in general cognitive ability

  35. Structural AsymmetryMethods • Design: 2 (structure) x 2 (task demand) x 2 (time) • Sample: 63 4-person teams • Task: DDD (MSU) • Measures: • Cognitive Ability (Wonderlic) • Team Performance (DDD output)

  36. Structural AsymmetryResults • H1: At time 1, functional structures were superior in predictable environments while divisional structures were superior in random environments (ΔR2 = .08, p < .05) • H2: At time 2, teams that switched from Fun. to Div. structures outperformed teams who switched from Div. to Fun. Structures (ΔR2 = .06, p < .05) • H3: Coordination behaviors mediated the relationship between structure and performance such that main effect of structural change on performance at time 2 was no longer significant when communication and coordination behaviors were controlled for

  37. Structural AsymmetryResults

  38. Dimensions of Structure

  39. Centralization Structures (Ellis et al., 2004) • Built on notion of asymmetric adaptability by examining centralization as structure • Vertical/role structure mode (centralization) rather than horizontal/task mode (departmentation) • Centralized: A designated leader has a degree of authority and control • Ensure coordination • Better in task conditions that require error control • Decentralized: Team members have authority to make individual decisions • Ease of learning/adapting • More innovative • Better in environments that demand speed or learning

  40. Centralization Structures Theory • Norms developed initially may impact future performance • In centralized structures, norms are built for coordination • These should lead to higher accuracy, which may carry over when teams switch structures • In decentralized structures, norms are built for independence and personal discretion • These should lead to higher speed, but may be harmful when the team switches structures and they are removed

  41. Centralization Structures Hypotheses • H1a: At time 1, teams with a centralized structure will be more accurate than teams with a decentralized structure • H1b: At time 1, teams with a decentralized structure will be faster than teams with a centralized structure • H2: Teams switching from Cen to Decen structures will be more successful at time 2 than teams switching from Decen to Cen structures • i.e. retain accuracy and gain speed vs. lose speed but do not gain accuracy

  42. Centralization Structures Methods • Design: 2 (structure) x 2 (time) between • Sample: 93 4-person teams • Task: DDD (MSU) with mixed task environment (environment held constant) • Measures: • Performance (DDD output) • Speed • Accuracy

  43. Centralization Structures Results • H1a: Centralized teams were more accurate than decentralized teams at time 1 (ΔR2 = . 30, p < .05) • H1b: Decentralized teams were faster than centralized teams at time 1 (ΔR2 = .11, p < .05) • H2: Teams switching from Cen to Decen gained accuracy, but did not lose speed. Teams switching from Decen to Cen did not gain accuracy, but lost speed

  44. Mechanistic vs. Organic Structures(Jundt et al., 2004) • Redundant • Horizontal and vertical structure are parallel • Costs and benefits of both types of structures are similar • Complimentary (hybrid) • Horizontal and vertical structures compliment each other • Can reap the benefits associated with both types of structures simultaneously

  45. Fun Cen Div Cen Fun Decen Div Decen Mechanistic vs. Organic StructuresTheory

  46. Mechanistic vs. Organic StructuresTheory • Teams having members with certain characteristics may be better able to make the necessary adjustments needed when changing structures. • May be especially true for the difficult O  M shift • Emotional stability - Better able to deal with stress and anxiety • Extraversion – More assertive and talkative

  47. Mechanistic vs. Organic StructuresHypotheses • H1: Teams switching from MO structures will outperform teams switching from OM structures at time 2 • H2a: Hybrid teams will outperform mechanistic teams at time 1 • H2b: Hybrid teams will adapt to structural change better than OM teams at time 2 • H3: Teams with high mean levels of emotional stability will be able to more successfully make the organic to mechanistic (O  M) structural shift • H4: Teams with high mean levels of extraversion will be able to more successfully make the (O  M) structural shift

  48. Mechanistic vs. Organic StructuresResearch Design • 2 (Departmentation) x 2 (Centralization) between at time 1 • Within team shift on both dimensions of structure at time 2

  49. Mechanistic vs. Organic StructuresMethod • Sample: 64 4-person teams • Task: MSU-DDD with mixed task environment • Measures: • Team performance (DDD output) • Emotional Stability & Extraversion: NEO-PI-R (Costa & McCrae, 1992)

  50. Mechanistic vs. Organic StructuresResults • H1: M  O teams outperformed O  M teams at time 2, controlling for time 1 performance (b = 2.55, p < .01) • H2a: Hybrid teams outperformed mechanistic teams at time 1, (t [47] = 3.01, p <.01) • H2b: Controlling for time 1 performance, hybrid teams outperformed O  M teams at time 2 (b = 1.93, p < .01)

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