Team Adaptiveness in Dynamic Contexts: The Roles of Planning and Patterns

Lei, Zhike; Waller, Mary J.; Hagen, Jan L.; Kaplan, Seth A.

doi:10.5465/ambpp.2014.10777abstract

Cited by 24 publications

(51 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There is a small but growing stream of empirical literature on emergent patterns in teams (Lei et al, ; Stachowski et al, ; Zijlstra et al, ). We contribute to this literature by elucidating the nonlinear, complex, and dynamic nature of team action patterns and their influence on effectiveness in a work environment changing over time.…”

Section: Discussionmentioning

confidence: 99%

“…Stachowski and colleagues found that in nonroutine situations, higher performing nuclear power plant crews exhibited fewer, shorter, and less complex interaction patterns. Similarly, Lei, Waller, Hagen, and Kaplan () found that crews with patterns that were shorter, simpler, and involved lower reciprocity outperformed other crews during a nonroutine situation. This suggests that patterns established that were effective in the prechange situation may actually become a liability as teams may have difficulty abandoning patterns that have been previously experienced as successful (Audia et al, ; Cohen & Bacdayan, ).…”

Section: Theoretical Framework and Hypothesesmentioning

confidence: 90%

“…Consistent with previous studies on interaction patterns in teams (Lei et al, ; Stachowski et al, ; Zijlstra et al, ), we used THEME (Magnusson, ), a pattern recognition software algorithm, to identify recurrent sequences of actions in the sequential behavioral data. The THEME algorithm uses a stepwise hierarchical procedure to identify patterns.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Fluid and stable: Dynamics of team action patterns and adaptive outcomes

2018

Self Cite

View full text Add to dashboard Cite

The current study draws on work in the areas of team adaptation, team compilation, and small groups as complex systems to predict and test relationships between time, taskwork team mental models, team action patterns, and team effectiveness. Three-person teams performed 9 scenarios of a firefighting simulation distributed over 3 days with discontinuous task changes introduced in the fourth and seventh scenarios (N = 41 teams; 123 individuals). We applied pattern detection algorithm software to the behavioral data to identify emergent performative patterns in the team members' task-oriented actions. We also used discontinuous growth modeling to track the development of these team action patterns and their dynamic relation to team effectiveness.The results indicate that pattern emergence increased over time. This was particularly true for teams with similar taskwork mental models, and these teams also showed a more acute decrease in action patterns after a task change. In addition, team action patterns became increasingly positively related to team effectiveness over time, but this effect was reset after the occurrence of a task change. Overall, our research provides practical guidance to managers by illustrating the value of teams having highly shared taskwork team mental models and of enhancing the effects of teams' action patterns on team adaptive outcomes.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Theoretical Framework and Hypothesesmentioning

confidence: 90%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Fluid and stable: Dynamics of team action patterns and adaptive outcomes

2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…Similarly, findings from nuclear plant teams during a crisis simulation showed distinct differences in the temporal interaction patterns of high versus low performing teams (Stachowski, Kaplan, & Waller, 2009 ). Moreover, a recent study on airline crews in a flight simulator highlights the role of different interaction patterns for team performance during routine versus non-routine work situations, such that successful teams show more in-process planning behavior patterns during routine versus non-routine situations (but only up to a point, i.e., U-shaped relationship between planning behavior patterns and performance; Lei, Waller, Hagen, & Kaplan, 2016 ).…”

Section: Detecting Patterns Of Behavior In Temporal Interactionsmentioning

confidence: 99%

“…Second, scholars should acknowledge and build upon the already existing studies that use the methods and tools discussed in this methods corner. A number of researchers and scholars have been using dynamic social interaction analysis techniques for quite a few years, particularly in research on team processes but increasingly also when considering leader-follower dynamics in organizations (e.g., Kolbe et al, 2014 ; Lei et al, 2016 ; Meinecke et al, 2017 ). These studies provide a nice base from which researchers new to these methods can draw considerable methodological advice and guidance as they study new areas using similar methods.…”

Section: Key Takeawaysmentioning

confidence: 99%

Modeling Temporal Interaction Dynamics in Organizational Settings

Lehmann‐Willenbrock

Allen

2017

J Bus Psychol

View full text Add to dashboard Cite

Most workplace phenomena take place in dynamic social settings and emerge over time, and scholars have repeatedly called for more research into the temporal dynamics of organizational behavior. One reason for this persistent research gap could be that organizational scholars are not aware of the methodological advances that are available today for modeling temporal interactions and detecting behavioral patterns that emerge over time. To facilitate such awareness, this Methods Corner contribution provides a hands-on tutorial for capturing and quantifying temporal behavioral patterns and for leveraging rich interaction data in organizational settings. We provide an overview of different approaches and methodologies for examining temporal interaction patterns, along with detailed information about the type of data that needs to be gathered in order to apply each method as well as the analytical steps (and available software options) involved in each method. Specifically, we discuss and illustrate lag sequential analysis, pattern analysis, statistical discourse analysis, and visualization methods for identifying temporal patterns in interaction data. We also provide key takeaways for integrating these methods more firmly in the field of organizational research and for moving interaction analytical research forward.

show abstract

Toward the incorporation of temporal interaction analysis techniques in modeling and understanding sociotechnical systems

David

Schraagen

Endedijk

2021

Hum Ftrs & Erg Mfg Svc

View full text Add to dashboard Cite

The increased complexity of modern sociotechnical systems (STS) necessitates the need for a manageable representation of their attributes, to augment our understanding and enable the development of ways through which we can increase their effectiveness, efficiency, and safety. Although many of the methodologies developed in the Human Factors domain map and investigate system properties and network structures, the inclusion of the temporal dimension in the analysis of STS remains limited. In this paper we present how modeling and visualization of STS can be augmented with the incorporation of temporal interaction analysis techniques that enable a micro-level, fine-grained analysis of data. We provide an overview of temporal analysis techniques by breaking down their main function, requirements, types of research questions they can address, and the visualization properties they offer, attempting to enhance their use in system analysis. This overview can assist researchers in selecting an analysis technique, enabling the incorporation of temporality in STS analysis, and helping towards the design of improved and safer systems and interventions.

show abstract

Team Adaptiveness in Dynamic Contexts: The Roles of Planning and Patterns

Cited by 24 publications

References 0 publications

Fluid and stable: Dynamics of team action patterns and adaptive outcomes

Fluid and stable: Dynamics of team action patterns and adaptive outcomes

Modeling Temporal Interaction Dynamics in Organizational Settings

Toward the incorporation of temporal interaction analysis techniques in modeling and understanding sociotechnical systems

Contact Info

Product

Resources

About