Does Overlap in Team Member Knowledge Predict Team Performance?

Blickensderfer, Beth; Cannon‐Bowers, Janis A.; Salas, Eduardo

doi:10.1177/1071181397041002217

Cited by 5 publications

(16 citation statements)

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“…In terms of the methodological contribution of the present effort, we contend that these results replicate and extend, in a real-world setting, earlier work done with simpler tasks and in laboratory settings (Blickensderfer, Cannon-Bowers & Salas, 1997;Ricci, et.al., 1997;Stout, 1995). Two Pathfinder indices, the degree to which knowledge structures were internally consistent and the degree to which team members shared common knowledge structures, varied in systematic, and predictable fashion.…”

Section: Hypothesissupporting

confidence: 85%

Assessing Team Knowledge Structures: Findings from the Field

Gualtieri

Burns

Phipps

et al. 1998

Proceedings of the Human Factors and Ergonomics Society Annual

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The factors that impact teams' cognitive representations of the systems with which they interact is an area of concentrated research effort. Not surprisingly, research indicates that these cognitive representations impact the team's functioning with the system. Despite the importance of these cognitive representations and their impact on performance, valid and reliable measurement in naturalistic environments remains elusive. Validity and reliability of a measure are especially important to assess the impact of training. The purpose of the current effort is to evaluate the efficacy of a particular knowledge elicitation and representation methodology. A demonstration of this methodology will be presented using data collected from the command and control elements of a Division Artillery (DIVARTY) command staff. Results indicate that this methodology distinguishes differences in team members' mental models as a function of expertise and subteam membership. Implications of these differences for training are discussed, as well as directions for future research,

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Section: Hypothesissupporting

confidence: 85%

Assessing Team Knowledge Structures: Findings from the Field

Gualtieri

Burns

Phipps

et al. 1998

Proceedings of the Human Factors and Ergonomics Society Annual

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“…TPM 11,1/2 Researchers have suggested that shared mental models may evolve to a higher efficiency level as the team matures and shares more experiences . The literature also supports the idea that team mental models can evolve over time through a process of progressive convergence or overlap of the models of individual team members (Blickensderfer et al, 1997;Glickman et al, 1987). In a similar vein, mental models are believed to evolve from a novice state to an expert state as an individual or team gains experience and refines the model (Gualtiere et al, 1996;Klimoski and Mohammed, 1994).…”

Section: Mental Modelsmentioning

confidence: 90%

Improving team decision‐making performance with collaborative modeling

Jeffery

Maes

Bratton‐Jeffery

2005

Team Performance Management: An International Journal

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -This article aims to examine considerations and strategies for improving team performance in decision-making by teaching teams to use collaborative modeling based on team mental models. Design/methodology/approach -The article describes the nature of shared mental models and collaborative modeling, the potential effects of collaborative modeling on team performance, and a perspective on communication imperatives that facilitate collaborative modeling. The articles builds upon this information to suggest five imperatives for teams to help them develop collaborative modeling skills Findings -The article offers strategies in the form of five imperatives for teams to observe in order to build skills in collaborative modeling and improve team performance by improving team members' ability to effect collaborative modeling to accomplish team tasks and goals. Originality/value -Research over the years in mental modeling and communication has created a powerful argument that effective communication and shared mental models improves team performance. However there is little about application of this concept in the literature. The next step for researchers is to develop application models for collaborative modeling and test those models through empirical research. This paper offers an application model based on imperatives to be observed by decision-making teams in order to facilitate the creation of shared mental models of team tasks and processes.

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“…There are many ways to aggregate, although most researchers have averaged the individual data (Blickensderfer et al, 1997a(Blickensderfer et al, , 1997bJenkins & Rentsch, 1995;Kraiger et al, 1996). However, the danger in averaging is that because of team member variance, the averaged result might be unrepresentative of any single team member.…”

Section: Aggregation Methodsmentioning

confidence: 98%

“…The knowledge possessed by effective teams has been frequently referred to as shared knowledge and, in similar contexts, as shared mental models, shared cognition, and shared understanding (Blickensderfer, Cannon-Bowers, & Salas, 1997b;Cannon-Bowers et al, 1993;Converse, Cannon-Bowers, & Salas, 1991;Klimoski & Mohammed, 1994;Kraiger, Krause, & Hart, 1996;Kraiger & Wenzel, 1997;Orasanu, 1990;Rentsch & Hall, 1994;Robertson & Endsley, 1997;Rouse, Cannon-Bowers, & Salas, 1992;Sarter & Woods, 1991;Stout et al, 1996). Such knowledge sharing is thought to help teams coordinate implicitly when explicit communications are hampered, thereby enhancing team performance (Cannon-Bowers et al, 1993;Kleinman & Serfaty, 1989;Stout et al, 1996).…”

Section: Team Knowledge: a Definitionmentioning

confidence: 99%

“…With enough structure, a structured interview can be converted into a paper-andpencil measure such as a survey or questionnaire, which are often easier to administer than interviews. In fact, some investigators have used structured interviews in the form of written questionnaires to elicit team knowledge (Blickensderfer, Cannon-Bowers, & Salas, 1997a;Blickensderfer et al, 1997b;Jenkins & Rentsch, 1995).…”

mentioning

confidence: 99%

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Measuring Team Knowledge

et al. 2000

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Multioperator tasks often require complex cognitive processing at the team level. Many team cognitive processes, such as situation assessment and coordination, are thought to rely on team knowledge. Team knowledge is multifaceted and comprises relatively generic knowledge in the form of team mental models and more specific team situation models. In this methodological review paper, we review recent efforts to measure team knowledge in the context of mapping specific methods onto features of targeted team knowledge. Team knowledge features include type, homogeneity versus heterogeneity, and rate of knowledge change. Measurement features include knowledge elicitation method, team metric, and aggregation method. When available, we highlight analytical conclusions or empirical data that support a connection between team knowledge and measurement method. In addition, we present empirical results concerning the relation between team knowledge and performance for each measurement method and identify research and methodological needs. Addressing issues surrounding the measurement of team knowledge is a prerequisite to understanding team cognition and its relation to team performance and to designing training programs or devices to facilitate team cognition.

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Does Overlap in Team Member Knowledge Predict Team Performance?

Cited by 5 publications

References 0 publications

Assessing Team Knowledge Structures: Findings from the Field

Assessing Team Knowledge Structures: Findings from the Field

Improving team decision‐making performance with collaborative modeling

Measuring Team Knowledge

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