Academic journal article Human Factors

Effects of Workload and Structure on Team Processes and Performance: Implications for Complex Team Decision Making

Academic journal article Human Factors

Effects of Workload and Structure on Team Processes and Performance: Implications for Complex Team Decision Making

Article excerpt


The prevalence of teams in numerous operational and organizational settings, coupled with increased technological advancements and system complexity, have enhanced the importance of team performance as an area for psychological research. The tactical decision-making environment is especially complex, demanding the effective performance of decision-making teams. Past incidents have indicated all too clearly that unfortunate circumstances result when teams commit decision-making errors.

Driskell and Salas (1991) noted that these complex technologies are paradoxical in that they simultaneously extend operator capabilities and increase the potential for catastrophic circumstances. These researchers argued that although there has always been a requirement for effective performance, the characteristics of modern systems have increased both the stress under which teams are required to perform and the severity of the consequences for inadequate performance in complex team decision-making settings.

A team is defined as a set of two or more individuals working in an interdependent fashion toward a common and meaningful goal (Morgan, Glickman, Woodard, Blaiwes, & Salas, 1986); thus the very nature of team performance demands that individuals strive to perform team tasks effectively under potentially stressful circumstances while also maintaining their individual task performance. These factors might be especially salient in distributed team decision making, in which individuals must interact quickly to communicate critical information. Furthermore, in complex decision-making environments, these tasks must be accomplished under conditions such as information ambiguity, rapid change and evolution of information, high time pressure, and high workload (Orasanu & Salas, 1993). In order to optimize the performance of teams in such environments, there is a need for research on the component processes of complex team decision making and how they are influenced by critical variables.

The Role of Resource Allocation in Complex Team Decision Making

According to Orasanu (1990), complex team decision making has four components: situation assessment, metacognition, shared interpretations of the problem at hand, and resource allocation. Of these actions, the continuous management and allocation of resources among individual members is unique to the team situation and, according to Salas, Dickinson, Converse, and Tannenbaum (1992), is one of the criteria that define a team. Clearly, the term resources refers to generic materials, the more specific nature of which depends on the task the team is performing. The term resource allocation, therefore, refers to the process by which a team monitors the resource needs of each team member in order to achieve an optimal distribution among individual members that allows the team to maximize its collective performance. Because resource allocation is an integral component of effective team performance in any operational setting, research is needed that provides insight into resource allocation, particularly the degree to which it is influenced by factors common to complex settings.

Given the complexity of real-world environments, research that allows for the manipulation and control of variables prevalent in these settings would be beneficial to the state of the art. Although operational settings and laboratory research seem to be mutually exclusive terms, it has been argued that the ultimate utility of lab research on team decision making lies in the extent to which the paradigm employed possesses the essential characteristics of the practical environment of interest (Orasanu & Salas, 1993). If a given lab study appropriately represents the majority of the essential features of the real world - such as being dynamic, uncertain, and highly demanding (see Orasanu & Connolly, 1993, for specific criteria) - then it can yield hypotheses that can be further tested in the field. …

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