There is a common expression in sports, “while individuals may play the game, a team wins a championship.” This expression not only applies to teams in sports, but many businesses as well. It is through the collaborative efforts of a team, that individual talent becomes collective excellence. The benefit of teamwork is immeasurable. With teams, individuals come together to support one another. Likewise, servant leadership offers a similar leadership perspective with supportive relationships and environments. Although servant leadership and team leadership have their differences, both focus on joint participation toward improvements within leadership settings.
This week, you explore leadership perspectives related to team and servant leadership. You examine how both theories of leadership provide collaboration between a leader and his or her followers and consider how a leader’s effectiveness relates to the group’s reliance on one another for success.
Learning Objectives
Evaluate team leadership
Nahavandi, A. (2014). The art and science of leadership(7th ed.). Upper Saddle River, NJ: Pearson. Chapter 6, “Current Era in Leadership”Chapter 8, “Leading Teams”Anonson, J. M. S., Ferguson, L., Macdonald, M. B., Murray, B. L., Fowler-Kerry, S., & Bally, J. M. G. (2009). The anatomy of interprofessional leadership: An investigation of leadership behaviors in team-based health care. Journal of Leadership Studies, 3(3), 17-25.Ilgen, D. R., Hollenbeck, J. R., Johnson, M., & Jundt, D. (2005). Teams in organizations: From input-process-output models to IMOI models. Annual Review of Psychology, 56(1), 517-543.van Dierendonck, D. (2011). Servant leadership: A review and synthesis. Journal of Management, 37(4), 1228-1261.
Optional Resources
Harvard Business Review. (2011). Leading collaborative groups [Video file]. Retrieved from
In order to effectively function as a team, leaders need to come together and think as a team. For many collaborative leadership teams, this may be a challenge to overcome. As you have learned in this course, often certain qualities or skills separate leaders from a collective group. As a result, leaders take the initiative to enact policies for change. Ironically, when functioning as a team, individualized leadership characteristics and skills are deferred for team decision making and group-identified goals. While team leadership presents benefits in leading an organization, notable challenges also exist within the theory.
For this Discussion, consider some of the unique characteristics of team leadership. Using the Learning Resources, reflect on the challenges associated with team leadership and consider whether or not team leadership may actually exist within organizations.
Posta description of team leadership and its characteristics. Then, describe two challenges teams may face when leading an organization. Finally, explain whether team leadership is an effective approach. Justify your response.
Discussion: Two Heads Are Better Than One—Team Leadership in Public Health
In order to effectively function as a team, leaders need to come together and think as a team. For many collaborative leadership teams, this may be a challenge to overcome. As you have learned in this course, often certain qualities or skills separate leaders from a collective group. As a result, leaders take the initiative to enact policies for change. Ironically, when functioning as a team, individualized leadership characteristics and skills are deferred for team decision making and group-identified goals. While team leadership presents benefits in leading an organization, notable challenges also exist within the theory.For this Discussion, consider some of the unique characteristics of team leadership. Using the Learning Resources, reflect on the challenges associated with team leadership and consider whether or not team leadership may actually exist within organizations.Posta description of team leadership and its characteristics. Then, describe two challenges teams may face when leading an organization. Finally, explain whether team leadership is an effective approach. Justify your response. Servant Leadership: A Review and Synthesis
Dirk van Dierendonck
First Published September 2, 2010 Review Article
https://doi-org.ezp.waldenulibrary.org/10.1177/0149206310380462
Article information
Abstract
Servant leadership is positioned as a new field of research for leadership scholars.
This review deals with the historical background of servant leadership, its key
characteristics, the available measurement tools, and the results of relevant studies
that have been conducted so far. An overall conceptual model of servant leadership
is presented. It is argued that leaders who combine their motivation to lead with a
need to serve display servant leadership. Personal characteristics and culture are
positioned alongside the motivational dimension. Servant leadership is demonstrated
by empowering and developing people; by expressing humility, authenticity,
interpersonal acceptance, and stewardship; and by providing direction. A high-quality
dyadic relationship, trust, and fairness are expected to be the most important
mediating processes to encourage self-actualization, positive job attitudes,
performance, and a stronger organizational focus on sustainability and corporate
social responsibility.
Keywords servant leadership, review, positive organizational behavior
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10.1146/annurev.psych.56.091103.070250
Annu. Rev. Psychol. 2005. 56:517–43
doi: 10.1146/annurev.psych.56.091103.070250
c 2005 by Annual Reviews. All rights reserved
Copyright
First published online as a Review in Advance on October 5, 2004
TEAMS IN ORGANIZATIONS: From
Input-Process-Output Models to IMOI Models
Daniel R. Ilgen,1 John R. Hollenbeck,2 Michael Johnson,2
and Dustin Jundt1
1
Department of Psychology, 2Department of Management, Michigan State University,
East Lansing, Michigan 48824; email: Ilgen@msu.edu, jrh@msu.edu,
John1781@msu.edu, jundtdus@msu.edu
Key Words teamwork, workgroup, groups, coordination, cooperation
■ Abstract This review examines research and theory relevant to work groups and
teams typically embedded in organizations and existing over time, although many studies reviewed were conducted in other settings, including the laboratory. Research was
organized around a two-dimensional system based on time and the nature of explanatory mechanisms that mediated between team inputs and outcomes. These mechanisms
were affective, behavioral, cognitive, or some combination of the three. Recent theoretical and methodological work is discussed that has advanced our understanding of
teams as complex, multilevel systems that function over time, tasks, and contexts. The
state of both the empirical and theoretical work is compared as to its impact on present
knowledge and future directions.
CONTENTS
INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
STRUCTURING THE CURRENT REVIEW: BEYOND THE
INPUT-PROCESS-OUTPUT FRAMEWORK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
FORMING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Trusting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Structuring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
FUNCTIONING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Bonding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Adapting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
FINISHING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
CONCLUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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INTRODUCTION
Over a decade ago, Levine & Moreland’s (1990) Annual Review of Psychology
chapter concluded that small groups/teams research was “alive and well, but living
elsewhere” (p. 620)—in organizational, not social, psychology. Guzzo & Dickson
(1996) made a similar observation, and Sanna & Parks (1997) documented this
empirically with an analysis of the top three organizational psychology journals.
Between 1996 and 2004 the trend continued.
The organizational domain has shown some shift from questions of what predicts team effectiveness and viability to more complex questions regarding why
some groups are more effective than others. We review what has been learned over
the past seven years by categorizing findings in terms of their relevance to the formation, functioning, and final stages of teams’ existence. From the outset we note
that whereas there seems to be consensus on the need to study affective, cognitive,
and behavioral mediational processes, this effort has been somewhat fragmented
and noncumulative due to a proliferation of constructs with indistinct boundaries
at the conceptual level and item overlap between measures of constructs at the
level of individual studies.
As is often the case for Annual Review authors, we struggled with the boundaries
of our domain. One aspect of this struggle is the recognition that there have been a
number of both methodological and substantive achievements over the last seven
years, but in the limited amount of space we have here, we focused primarily
on substantive studies. This should not obscure the fact that during the period
covered by the review, several important methodological developments took place,
including major shifts toward (a) multilevel theoretic and analytic techniques (see
Klein & Kozlowski 2000), (b) complex computer-generated task environments that
simulate real-world phenomena while objectively capturing and time-stamping
team behaviors (Schiflett et al. 2004), (c) the appearance of computational and
mathematical models that provide potential for means of addressing the dynamic
complexity of teams (Coovert & Thompson 2000, Losada 1999), and (d) the use
of social network analysis to investigate the effects of larger social patterns on
between-team and within-team behavior (e.g., Baldwin et al. 1997, Burt 2000,
Hinds et al. 2000).
In terms of content, two recent Annual Review of Psychology chapters (Guzzo &
Dickson 1996, Kerr & Tindale 2004) were instrumental in establishing boundaries.
Guzzo & Dickson’s (1996) chapter provided a clear beginning date for our review. It
also provided excellent guidance for content inclusion with its focus on work teams,
particularly teams embedded in ongoing organizations with pasts and futures. We
share the concern for teams in similar contexts, but unlike Guzzo & Dickson,
we did not limit the research setting to field research if we felt the empirical
observations were relevant to work teams. Kerr & Tindale’s (2004) Annual Review
of Psychology chapter reviewed the social psychological literature on small group
performance and decision making, which provides an up-to-date source for that
content and allows us to ignore work addressed by them.
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STRUCTURING THE CURRENT REVIEW: BEYOND
THE INPUT-PROCESS-OUTPUT FRAMEWORK
Conceptually, team researchers have converged on a view of teams as complex,
adaptive, dynamic systems (McGrath et al. 2000). They exist in context as they
perform across time. Over time and contexts, teams and their members continually
cycle and recycle. They interact among themselves and with other persons in contexts. These interactions change the teams, team members, and their environments
in ways more complex than is captured by simple cause and effect perspectives.
A number of excellent theoretical models of teams have appeared recently.
McGrath et al. (2000) describe three levels of dynamic causal interactions (local,
global, and contextual). Kozlowski and colleagues’ (Kozlowski et al. 1999) theory
of compilation and performance describes inputs, processes, and outcomes that
develop over time as teams interact in contexts that are both external environments
of the team and are shaped by actions of the teams in a reciprocal causal fashion.
Knowledge, attitudes, and behaviors are both inputs and processes in a developmental sequence that impacts team performance. Team performance, while an
output at time tn, is an input and a part of the process leading to performance output at time tn+1. A similar metatheoretical position, with processes unfolding over
time, served as an underpinning for Marks et al.’s (2001) taxonomy of team processes and DeShon et al.’s (2004) multigoal study. Although these models contain
differences in specific details regarding the nature of teams, all reflect the underlying notion that teams are complex, dynamic systems, existing in larger systemic
contexts of people, tasks, technologies, and settings.
The empirical research on teams in organizational contexts is also moving in
the direction of increased complexity, but this work still has a way to go to match
developments in the conceptual domain. However, the empirical literature in the
past six years does differ from that which preceded it. Prior to 1996, much of the
empirical research on teams was focused on the outcomes of team performance
and viability. This research was guided by practical issues: The search was for
answers to the generic question of what makes some teams more effective or
more viable relative to others, and it emphasized inputs such as composition,
structures, or reward allocations. Over the past six years, more attention was paid
to mediating processes that explain why certain inputs affect team effectiveness and
viability.
In one sense, this search for mediators was well informed by previous attention
to process as the link between inputs and outputs. Classic works of Steiner (1972),
McGrath (1984), and Hackman (1987) expressed the nature of team performance
in classic systems model ways in which inputs lead to processes that in turn
lead to outcomes (the input-processes-output, or I-P-O, model). This framework
has had a powerful influence on recent empirical research, much of which either
explicitly or implicitly invokes the I-P-O model. In another sense, however, the
convergence on consensus regarding the utility of I-P-O models as a guide to
empirical research fails to capture the emerging consensus about teams as complex,
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adaptive systems. Indeed, the I-P-O framework is insufficient for characterizing
teams (Moreland 1996), and the most recent team literature, in at least three specific
ways.
First, many of the mediational factors that intervene and transmit the influence
of inputs to outcomes are not processes. Marks et al. (2001) developed a temporally
based framework and taxonomy of team processes and correctly noted that many
constructs presented by researchers trying to invoke the I-P-O model as process
are not really process at all, but emergent cognitive or affective states. Their solution to the imprecision in the use of the term team process was to exclude from
their review of team process all constructs that fit their emergent state definition
rather than process definition as they developed their team process taxonomy. This
strategy, while useful for their purpose of isolating a subset of conceptually pure
behavioral processes, was not sufficient for our task of reviewing the broader teams
literature, a domain including both behavioral processes and emergent cognitive
and affective states.
Second, an I-P-O framework limits research by implying a single-cycle linear
path from inputs through outcomes, even though the authors of the classic works
clearly stipulated the potential for feedback loops, and some (e.g., Hackman 1987,
McGrath et al. 2000) explicitly recognized limits of I-P-O thinking. Yet, failure
to identify the feedback loop in the I-P-O sequence is likely to have limited the
development of I-P-O-focused team research more than would have resulted with
the use of a different model. Indeed, research that is more recent has examined
traditional “outputs” like team performance and treated them as inputs to future
team process and emergent states.
Finally, the I-P-O framework tends to suggest a linear progression of main effect
influences proceeding from one category (I, P, or O) to the next. However, much
of the recent research has moved beyond this. Interactions have been documented
between various inputs and processes (I x P), between various processes (P x P),
and between inputs or processes and emergent states (ES) (Colquitt et al. 2002, De
Dreu & Weingart 2003, Dirks 1999, Janz et al. 1997, LePine et al. 1997, Simons
et al. 1999, Simons & Peterson 2000, Stewart & Barrick 2000, Taggar 2002, Witt
et al. 2001). Emergent states are constructs that develop over the life of the team
and impact team outcomes. The broader focus beyond simply inputs and process
places attention on boundary conditions of the traditional I-P-O framework and
highlights when, where, and with whom various processes and emergent states
become relevant.
Thus, the I-P-O framework is deficient for summarizing the recent research and
constrains thinking about teams. As an alternative model, we use the term IMOI
(input-mediator-output-input). Substituting “M” for “P” reflects the broader range
of variables that are important mediational influences with explanatory power for
explaining variability in team performance and viability. Adding the extra “I” at
the end of the model explicitly invokes the notion of cyclical causal feedback.
Elimination of the hyphen between letters merely signifies that the causal linkages
may not be linear or additive, but rather nonlinear or conditional.
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In keeping with the temporal features of many recent approaches, we initially
organized the review around studies that focus on the early stages of team development (i.e., the IM phase), labeled the Forming Stage, followed by those examining
issues that we see as the team develops more experience working together (i.e., the
MO phase), labeled the Functioning Stage, and finally the Finishing Stage (i.e., the
OI phase), where the team completes one episode in the developmental cycle and
begins a new cycle. The paucity of literature directed at decline led us to collapse
over the three in the finishing phase. Our use of the verb form throughout the
review is intentional, to emphasize how these processes and states extend through
time and involve change (Weick 1969). Within the three-way temporal classification, we added another three-way categorization scheme that reflects whether the
primary interest of the study deals with affective, behavioral, or cognitive aspects
of team development. In the formation phase, the topic of trusting focused on affective mediators, planning behavioral ones, and structuring cognitive ones. In the
functioning phase, affect, behavior, and cognition were discussed under bonding,
adapting, and learning, respectively. We emphasize that use of these categorical labels, while reflective of the dominating affective, behavioral, or cognitive process,
was not meant to imply that other processes were excluded. Often all processes
were present in any one category. For example, trusting involves not only affect
but also cognitions and behavioral intentions. In sum, we present here a 3 × 3
framework in an effort to capture the domain or research on teams, not to suggest
that the organizing model is a theory of team behavior.
FORMING
Trusting
For team members to trust in the team, they must feel that (a) the team is competent
enough to accomplish their task (in the literature we reviewed, this is expressed in
terms of constructs such as potency, collective efficacy, group efficacy, and team
confidence), and (b) that the team will not harm the individual or his or her interests,
which we refer to as safety.
Potency is the team member’s collective belief that they can be effective
(Guzzo et al. 1993). Campion et al. (1996) found potency was positively related to
employee self-ratings of effectiveness, manager judgments of team performance,
and group performance appraisals conducted by their organization. Similarly,
Hyatt & Ruddy (1997) found that work group confidence was positively related
to managerial ratings of group performance on a number of different objective
measures. Little & Madigan (1997) found that collective efficacy was positively
related to a number of different group performance behaviors as well. Finally,
Seijts et al. (2000) examined how group-referenced individual ratings of group
efficacy differed from individually aggregated ratings of self-efficacy for multiple
trials on a mixed motive task.
POTENCY
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Many studies took a more complex approach to examining the relationship between potency-related constructs and team effectiveness. Hecht et al. (2002) found
potency predicted performance over and above group member ability, and group
goal commitment did not predict variance in performance over potency. Jung and
colleagues (Jung & Sosik 1999, Jung et al. 2002) tested a reciprocal model in
which group heterogeneity, preference for group work, outcome expectation, and
potency were suggested to be unique predictors of group performance. Group performance at Time 1 predicted each of these constructs and predicted performance
at Time 2. The major findings suggested a unique reciprocal relationship between
potency and group performance.
Using both a lab and a field sample, Chen et al. (2002) examined the relationships between team expertise, “team drive” (the team level analogue of achievement motivation), collective efficacy, and team performance. They found that “team
drive” positively and uniquely related to collective efficacy beliefs, whereas team
expertise did not. Collective efficacy predicted unique variance in team performance and team drive in the lab, but not in the field. Durham et al. (2000) found
that initial task performance related to group efficacy, and indirectly to group performance through the influence on goals and information seeking. Gibson (1999)
supported a contingency view in which collective efficacy exerted a positive influence on performance under conditions of low uncertainty, high task interdependence, and high collectivism.
For Gonzalez et al. (2003), task cohesion mediated the relationship between
collective efficacy and group effectiveness. Marks (1999) found that collective
efficacy was positively related to team performance in a routine task environment,
but not in a novel one. High levels of communication partially mediated the positive relationship between collective efficacy and team performance when the task
environment was controlled. Sivasubramaniam et al. (2002) found a reciprocal
relationship between transformational leadership and potency: Potency influenced
later performance where collective efficacy was referenced to the team’s specific tasks and potency to more generalized settings past, present, and future. Lee
et al. (2002) made a conscious distinction between potency and collective efficacy.
Controlling for group size and initial performance, group norm strength predicted
potency but not collective efficacy, and potency predicted Time 2 performance
on a novel task whereas collective efficacy did not. The data supported potency
and efficacy as different constructs. Finally, Gully et al. (2002) conducted a metaanalysis that examined the effects of both team efficacy and potency on performance. Their findings suggest that both team efficacy and potency are meaningful
predictors of team performance, and that the relationship between team efficacy—
but not potency—and performance was stronger when task interdependence was
high.
In addition to trusting the team’s competence, individuals must also
trust the member’s intentions. Jones & George (1998) distinguished between several different kinds of trust and suggested that levels of trust (or distrust) can be
SAFETY
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shaped by people’s values, attitudes, and moods/emotions, as well as by previous
experience. In turn, they suggested that unconditional trust, the kind most valuable
to teams, should have a strong direct, positive effect on interpersonal cooperation
and teamwork. Few studies have examined the impact of interpersonal trust-related
constructs on team effectiveness, and none have gone into the level of detail that
Jones & George supply in their theoretical piece. Edmondson (1999), however,
examined both collective efficacy and a trust-related variable she called psychological safety as they related to two structural variables (team leader coaching
and organizational contextual support), team learning behaviors, and team performance. She defined psychological safety as “a shared belief that the team is safe
for interpersonal risk taking” (p. 354). Her model suggested a causal sequence in
which the two structural variables led to higher psychological safety and team efficacy and, in turn, to greater team learning and performance. Psychological safety
and team efficacy mediated the relationships between the structural variables and
team learning, learning behaviors mediated the relationship between psychological safety and team performance, and team efficacy did not predict unique variance
in learning behaviors.
In a follow-up qualitative study, Edmondson et al. (2001) examined several
hospitals implementing new cardiac surgery technology. A key characteristic of
successful innovators was their ability to design preparatory practice sessions and
early trials that created a sense of psychological safety. In hospitals low in psychological safety, people were less likely to engage in risk taking, and they exhibited
more behaviors consistent with the status quo. Looking at both psychological and
physical safety, Hofmann & Stetzer (1996) found that feelings of psychological
safety led indirectly to actual physical safety through the mediating influence of
communication regarding unsafe acts.
Planning
Moving from the affective to the behavioral realm, at the early stages of team
development one key mediating variable that explains success and viability is the
degree to which the team arrives at an effective initial plan of behavioral action.
Effective planning has two related, and yet distinct, components. First, the team
needs to gather information that is available to the group members and/or their
constituencies. The group then must evaluate and use this information to arrive at
a strategy for accomplishing its mission.
The studies pertaining to gathering information have
focused on information sharing, information seeking, and communicating. Two
cross-sectional survey studies documented the importance of effective information gathering for team performance. Barry & Stewart (1997) correlated member
personality measures with open communication and team performance on student
projects. Although these authors failed to find the relationship they hypothesized
between group extraversion and open communication, they did report a significant
GATHERING INFORMATION
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relationship between open communication and team performance, as did Hyatt &
Ruddy (1997).
Drach-Zahavy & Somech (2001) examined the influence of functional diversity
on information exchange and innovativeness. Functional heterogeneity predicted
information exchange, and information exchange, in turn, was positively correlated
with team innovation. Bunderson & Sutcliffe (2002) distinguished between withinmember and between-member diversity. Within-person diversity reflects the fact
that each group member has had experience in different functional areas, and
between-person diversity means that each team member has a different functional
background. Information sharing was more effective in the teams that contained
within-person diversity, relative to between-person diversity, and this, in turn, was
related to higher team performance.
Two studies examined group voice, operationalized in this research as the extent
to which people speak up within their group (Erez et al. 2002, LePine & Van
Dyne 1998). LePine & Van Dyne found participation rates were higher for group
members who were (a) high in self-esteem, (b) male, (c) Caucasian, (d) high status,
(e) highly educated, ( f ) highly satisfied with their group, and (g) in smaller, selfmanaged teams. Those with low self-esteem exhibited especially low levels of
participation behavior in large groups and self-managed groups. Erez et al. (2002)
examined the role of participative behavior in a quasi-experiment where leaders
either rotated in or emerged and were evaluated either by peers or by external
sources. Rotation of the leader’s role and the provision of peer feedback promoted
higher participation levels and positively impacted performance.
Durham et al. (2000) examined the effects of group goals and time pressure
on information seeking and performance on a team decision-making task. These
authors found that group efficacy indirectly influenced information sharing through
group-set goal difficulty, which in turn had an indirect positive effect on group
performance through information-seeking behaviors.
Stout et al. (1999) examined the relationships between
strategy development, communicating, shared mental models (a construct that we
review in more detail below), and coordinated team performance on a helicopter
defense/surveillance simulation. Better strategy development led to greater levels
of unsolicited information sharing, more well developed team mental models, and
higher performance during high workload situations. Tesluk & Mathieu (1999) investigated teams that faced roadblocks or obstacles to goal accomplishment. Teams
that were most likely to overcome problems were those that anticipated problems
in advance and had contingency plans in place from the very beginning. Further,
crews with higher levels of coordination, potency, and familiarity (which they refer
to as teamwork processes) were more likely to develop effective strategies.
Effective strategy development is enhanced by unambiguous and well-prioritized goals and agreement on the best means of goal accomplishment. Pritchard
(1995) and his colleagues have developed and implemented a team-based performance management system called ProMES (productivity measurement and
DEVELOPING STRATEGY
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enhancement system) that focuses on identifying objective team outputs, as well
as the level of these outputs required to reach various levels of effectiveness for
the team. Teams receive feedback referenced to these outputs, and are encouraged
to develop plans that would help them achieve internally or externally set goals.
ProMES has been used in a wide variety of contexts to help improve team planning
and performance (Pritchard et al. 2001).
Structuring
Structuring refers to the development and maintenance of norms, roles, and interaction patterns in the teams. Two cognitive structuring constructs have dominated
the recent literature on teams. One is a shared mental model, which emphasizes
common cognitive elements among group members. The second set of studies
deals with transactive memory systems and emphasizes the unique and distinctive
cognitive elements among group members. Ironically, one of these literatures suggests that high performance results when group members share cognitive elements,
whereas the other suggests groups perform best when members compartmentalize
and specialize in different aspects of the cognitive space that the team is required
to cover.
Mohammed & Dumville (2001) defined shared mental
models as “organized understanding of relevant knowledge that is shared by team
members” (p. 89). The focus is on collective knowledge regarding what individual
team members hold in common. Whereas Mohammed & Dumville’s (2001) work
was conceptual in addressing the nature of the construct, others were concerned
with measuring it and treating its development as part of something that could be
addressed through training (e.g., Langan-Fox et al. 2000). Much of this work grew
out of the TADMUS (Tactical Decision Making Under Stress) project, which was
a response to the tragic shooting down of Iran Air Flight 655 by the USS Vincennes
over the Persian Gulf in 1988. The TADMUS project represented a convergence of
operational, scientific, and bureaucratic efforts (Collyer & Malecki 1998) to create
a partnership between behavioral scientists and operational naval personnel. The
result was the development of a process that embedded team training within the
dynamic task environment (Cannon-Bowers & Salas 1998). A number of principles
emerged from this and related work, particularly in connection to team training
(Kozlowski 1998, Kozlowski et al. 1999). The most important principle is that of
treating teams, rather than individuals, as the basic unit of analysis, and viewing
team members as active participants in a continuous learning process.
Marks et al. (2002) examined the role of shared mental models as a factor that
mediates the relationship between cross-training and team effectiveness. Crosstrained teams on a helicopter simulation were more likely to develop shared mental
models, and teams with shared mental models performed better. Better performance resulted because the teams were more likely to display effective coordination and team backup behaviors. Mathieu et al. (2000) found similar results
SHARED MENTAL MODELS
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with dyads performing a flight combat simulation. Again, coordination and communication mediated the relationship between the team mental model and team
performance.
Consistent with Wegner’s (1986) work, Austin (2003)
defined transactive memory as “a combination of the knowledge possessed by
each individual and a collective awareness of who knows what” (p. 866). In contrast to shared mental models, transactive memory focuses on who knows what
rather than on overlapping task- or team-relevant knowledge. Austin (2003) studied field groups in charge of launching different types of new products in a sporting goods/clothing company, and broke transactive memory into four elements:
knowledge stock (amount of knowledge), consensus (agreement on who knows
what), knowledge specialization (amount of redundancy), and accuracy (correctness of knowledge about what others know). Each facet was then examined for its
ability to predict unique variance in group goal attainment and both external and
internal evaluations of performance. Task transactive memory accuracy was related positively and uniquely to all three performance criteria, and task knowledge
specialization was related uniquely to both external and internal evaluations of
team performance. Similarly, Lewis (2003), with different subdimensions, found
transactive memory positively related to performance.
Two studies did not use the term transactive memory but did capture similar constructs. Druskat & Kayes (2000) assessed teams of MBA students on interpersonal
understanding—accurate understanding of the spoken and unspoken preferences,
concerns, and strengths of other members. Hyatt & Ruddy (1997) defined roles in
terms of knowledge structures to include both (a) common expectations regarding
work group behavior, and (b) knowledge about what members knew. Both studies
found their constructs related to team performance.
Finally, Hollenbeck et al. (2002) examined the impact of different role structures
on team performance via shared cognition. In divisional structures, team members
had broad roles and resources and were grouped by region, whereas team members
in a functional structure each had very narrow, specific roles, and were grouped by
resource or task. Results suggested that different types of role structures are better
suited for different types of environments. Divisional structures were thought to
promote the development of team mental models that were more complete, and
these models in turn led to better performance in random environments. On the
other hand, functional structures should promote the development of transactive
memory, thus leading to higher performance in predictable environments.
TRANSACTIVE MEMORY
FUNCTIONING
Bonding
Bonding reflects affective feelings that team members hold toward each other and
the team. Whereas trust represents a willingness to work together on the task,
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bonding goes beyond trust and reflects a strong sense of rapport and a desire
to stay together, perhaps extending beyond the current task context. We placed
studies that examined constructs such as group cohesiveness, team viability, social
integration, satisfaction with the group, person-group fit, and team commitment
under this heading because they share a common core that deals with the strength
of the member’s emotional and affective attachment to the larger collective (Bishop
& Scott 2000, Kristof-Brown et al. 2002). Because it takes time for team bonding
to occur, its effects typically are observed not in the early formative phase but in
the more mature functioning stage.
This is an important category of studies for three reasons. First, although past
research has suggested that bonding is not all that necessary for high levels of team
performance, more recent meta-analytic evidence suggests otherwise, particularly
when work-flow interdependence is high (Beal et al. 2003). Second, as noted in
a recent edited volume by Hinds & Kiesler (2002), organizations are increasingly
employing virtual teams whose members rarely meet face-to-face. Despite the rise
in their prevalence, the cumulative evidence from a recent meta-analysis of 27
studies questions the degree to which members of virtual teams ever bond with
one another in the traditional sense, and suggests that as a result, they are both
slower and less accurate than face-to-face teams (Baltes et al. 2002). A number of
elaborate interventions have been offered to help overcome this problem (Kraut
et al. 2002, Nardi & Whittaker 2002, Olson et al. 2002). Finally, even in contexts
that allow face-to-face interactions, attempts to implement team-based structures
meet resistance due to fears among leaders or members that they will not be able to
manage the conflict that arises from their differences (Kirkman & Shapiro 1997).
Conflict often starts small, but then spirals out of control, and in some cases even
results in violent reactions (Robinson & O’Leary-Kelly 1998) and withdrawal
behaviors (Duffy et al. 2000).
Although past research on composition
has generally conceived of teams as existing on a single continuum ranging from
demographically homogeneous to demographically heterogeneous, more recent
research has focused on specific aspects of demography. Riordan & Shore (1997)
showed that some demographic differences, such as race/ethnicity, were much
more important relative to age or gender when it came to predicting satisfaction
with the team, a finding later replicated by Pelled et al. (1999), who employed
emotional conflict as a criterion. Even within the race/ethnicity categories, it was
critical to distinguish among different minority groups (African American versus
Hispanic); without differentiation, a great deal of predictability is lost (Riordan
& Shore 1997). All of this suggests that the simple, nondelineated construct of
diversity that does not reflect the specific aspect of diversity embodied in the
group has little predictive or explanatory power.
Others have challenged the notion that diversity is a meaningful continuum, and
proposed that the opposite ends of the scale are qualitatively, not quantitatively,
different. Earley & Mosakowski (2000) showed that the key to team bonding
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was developing a single culture within the team, and this was promoted by either
homogeneous compositions or highly heterogeneous compositions. Worst were
moderately heterogeneous compositions that created subgroups or token members.
Polzer et al. (2002) also found that high levels of heterogeneity could be conducive
to developing cohesive teams.
Harrison and colleagues (1998, 2002) distinguished between surface-level diversity, which deals with demographic differences, and deep-level diversity, which
deals with differences in attitudes and values, and showed that the importance of
each varied with time. Surface-level diversity was more critical early, but its influence gave way to deep-level influence at later stages of the group’s development.
Jehn et al. (1999) distinguished between social category (demographic), value,
and informational diversity, and reported similar results. Over the course of team’s
development, value diversity had a much more deleterious effect on commitment
to the team relative to social category diversity.
Other research on bonding has examined diversity operationalized by differences in personality traits among team members. Barrick et al. (1998) found that
social cohesion was highest when teams were high on agreeableness, extraversion,
and high emotional stability. However, variance in agreeableness harmed cohesion,
variance in extraversion promoted cohesion, and variance in emotional stability
was unrelated to cohesion. Clearly, one must go beyond both demographic characteristics and simple, continuum-based hypotheses regarding homogeneity when
it comes to understanding the complexities of when and why teams bond.
Although Barrick et al. did not explicitly show why teams high on agreeableness,
emotional stability, and extraversion (and variance in extraversion) were better able
to bond, Keller (2001) showed that cross-functional teams create stress, which in
turn lowers cohesiveness. Teams high on emotional stability may weather this stress
better than teams that are low in this trait. Simons et al. (1999) showed that another
key to managing cross-functional teams is producing effective debate, which is
likely to be difficult to achieve in introverted teams or teams in which all members
are high in extraversion and thus fight for “airtime.” Finally, Chatman & Flynn
(2001) found that the speed with which demographically heterogeneous teams
developed cooperative norms was the best predictor of their eventual viability, and
this probably is related closely to the level and variability of agreeableness.
Several recent studies have examined interventions that might be used to minimize social conflict among team
members. Druskat & Wolff (1999) showed that face-to-face developmental feedback from peers could drastically reduce conflict, especially if this feedback is
delivered at the appropriate time (at the project’s midpoint). Naumann & Bennett
(2000) found that leaders who promote procedural justice and apply rules consistently were able to minimize relationship conflict. De Cremer & van Knippenberg
(2002) replicated and extended these findings regarding the leader’s role in minimizing relationship conflict. van der Vegt et al. (2001) showed that group satisfaction is also promoted by adopting group-level rewards that do not make fine
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distinctions among team members; the value of this, however, may be offset by
the fact that cooperative rewards sometimes are associated with higher levels of
social loafing (Beersma et al. 2003).
Although consensus exists regarding the deleterious effects of relationship conflict, this is not true with respect to task conflict. Jehn (1994) showed that there
was a +0.44 correlation between task conflict and team performance and a –0.45
correlation between relationship conflict and team performance. Unfortunately,
subsequent research failed to replicate the Jehn (1994) results. A recent metaanalysis, based upon 26 effect sizes, found the 95% confidence interval for the
relationship between task conflict and performance to be –0.13 to –0.26, making
the Jehn (1994) result an extreme outlier (De Dreu & Weingart 2003). Indeed, this
same meta-analysis estimated the correlation between task and relationship conflict
at over 0.50. The emerging consensus is that task conflict is generally unhelpful
for teams. Instead of task conflict, teams require (a) rich, unemotional debate in
a context marked by trust (Simons & Peterson 2000), (b) a context where team
members feel free to express their doubts and change their minds (Lovelace et al.
2001), and (c) an ability to resist pressures to compromise quickly (Montoya-Weiss
et al. 2001) or to reach a premature consensus (Choi & Kim 1999).
Adapting
Most of the recent literature we reviewed dealing with behavioral processes of
adapting falls under two distinct subcategories, one of which deals with performance in routine versus novel contexts, and the second dealing more narrowly
with one specific aspect of adaptability—workload sharing in the form of either
helping behaviors or backing up behaviors.
In a controlled laboratory setting, LePine (2003) extended research from the individual level to teams
and found teams with higher mean levels of cognitive ability and openness to experience did better when the task environment changed. Documenting differences
between variables that predict team performance under routine versus novel conditions was also the goal of a study by Marks et al. (2000), but this study examined
aspects of team training rather than team composition. Using a laboratory study
simulation, Marks et al. found that training aimed at increasing the team’s ability
to communicate and interact, as well as expanding communication from leaders,
improved team adaptability.
In a study by Waller (1999), the speed with which teams recognized that the
environment has changed was also shown to be critically important for improving
adaptability. This study employed airline crews that were observed on a realistic
flight simulator performing after a hydraulic failure caused an unexpected change
in the flight plan. Although previous research had documented that adaptability was
contingent on the team’s ability to reprioritize goals and redistribute tasks, Waller
(1999) found that it was the speed—not necessarily the frequency—with which
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teams engaged in these behaviors that was critical for adaptability. Methodologically, observing teams over time was critical; adapting would have been missed
with retrospective self-reports. It was the timing of the behaviors, not the behaviors
themselves, that was critical.
Subsequent research showed that the speed with which teams recognized the
need for change was related to the number of “interruptions” that caused them
to “stop and think” about their processes while engaged in the task (Okhuysen &
Waller 2002). In addition, specific instructions to team members to raise questions
helped adaptation (Okhuysen & Waller 2002), but did so less when teams members
had a previous history of working together (Okhuysen 2001). In familiar teams,
imposition of an external intervention disrupted established roles that already contained provisions for task interruptions. This effect is similar to that observed by
Arrow (1997), who showed that feedback about deteriorating performance was not
sufficient to get teams, entrained in their behavioral routines, to radically change
their processes. Harrison et al. (2003) revealed entrainment on repeated trials of
a task persisted even when a different type of task “interrupted” those repeated
trials.
Moon et al. (2004) showed that teams whose initial task experience took place
in a functional structure that created simple tasks with high interdependency requirements were fully able to switch to a divisional structure characterized by
increased task complexity and less interdependence when the situation demanded
such a change (Hollenbeck et al. 2002). However, teams that started out in divisional structure were not able to successfully execute a change to a functional
structure, even when changes in the task environment demanded such a reconfiguration. In this context, the norms of high communication and support behavior of
the formerly functional teams persisted into the future and promoted their adaptation to their new divisional structure. In contrast, the norms for concentration
and independence associated with the formerly divisional teams also persisted
into the future, destroying their ability to adapt to the new requirements of the
functional structure. This research implies that rather than conceptualizing adaptation as an all-or-nothing phenomenon (teams are either adaptable or not), a more
appropriate conceptualization would propose that adaptation is a directional phenomenon that needs to consider what the team is adapting from and what it is
adapting to.
One specific aspect of adaptation that has
received a great deal of attention recently is the degree to which team members
actively share their workload, help, or back up each other when faced with high
demands. The virtues of workload sharing are one of the critical reasons behind
adopting team-based structures (McIntyre & Salas 1995). Recent research supports
this position, but also qualifies it, suggesting that helping behavior is a doubleedged sword.
On the positive side, Podsakoff et al. (1997) examined the separate facets of
organizational citizenship, and found that the amount of helping behavior exhibited
HELPING AND WORKLOAD SHARING
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in the team was the only facet that had a positive impact on both the quality and
quantity of team performance. This facet of citizenship was more important than
facets such as civic virtue or sportsmanship.
Barrick et al. (1998) linked helping to team composition in a study of a large
number of manufacturing teams where they found teams that were high on conscientiousness, agreeableness, extraversion, and emotional stability provided more
help to one another relative to teams characterized in the opposite fashion. Moreover, on all four of these attributes, the score of the member lowest on the variable
provided better predictive value for helping behavior than the average- or highestscoring member for all four traits. This suggests that team members may only help
each other in a reciprocal fashion, making the team as a whole look more like its
worst member than its best member on this aspect of group process.
Another finding that emerged from the Barrick et al. (1998) study was that both
helping behavior and flexibility were negatively related to variance in the team
member’s levels of general cognitive ability, suggesting that when high-ability
members are teamed up with low-ability members, workload sharing is restricted
and perhaps unidirectional. Other studies employing very different samples and
methods have found that the frequency of helping behavior is negatively associated with team performance (Baldwin et al. 1997, Podsakoff & MacKenzie 1997).
Shedding light on this, Porter et al. (2003) directly tested this speculation in a study
that separated helping behaviors into two kinds—high-legitimacy helping behavior
that eliminated a true workload distribution problem, and low-legitimacy helping
behavior that simply reflected codependent enabling of “needy” team members.
Extraversion displayed both a main and an interactive effect on backing up behavior, indicating that those who were high in extraversion sought and received
much more help across all conditions, but especially when legitimacy was high.
Yet, there was no main effect whatsoever for people who were high in conscientiousness, those who were the most discriminating team members when it came to
helping. People who were high in conscientiousness were more likely to seek help
in the high-legitimacy condition, but less likely to seek help in the low-legitimacy
condition relative to those who were low in conscientiousness (thus showing no
main effect).
Although low legitimacy in the Porter et al. (2003) study was operationalized
in terms of a factor external to the team (objective workload distribution), a help
request might also be low in legitimacy if it originates from someone who is not
giving his or her best effort to the team. Research on social loafing continues to
demonstrate how sensitive team members are to suspected “shirking” on the part
of their teammates (Plaks & Higgins 2000). Indeed, LePine et al. (2002) found that
potential providers of helping behavior respond very differently to team members
who seem to need help because of a lack of ability, relative to team members who
seem to need help due to lack of effort. LePine & Van Dyne (1998) developed a
more comprehensive model of how teams react to their weakest link, noting how
characteristics of the low performer influence peers, and in turn determine the form
of helping intended to benefit the group.
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Learning
Learning is often a cognitive precursor to adaptation. The studies reviewed here
focus primarily on changes in the team’s knowledge base, rather than behavioral changes that may or may not flow from such learning. Within this category,
most of the recent literature we reviewed falls under two distinct subcategories:
(a) learning from team members who are minorities (defined in many different
ways) and (b) learning who is the best team member for specific tasks and capitalizing on this knowledge.
Arguments for
team-based organizational structures are often predicated on the belief that different team members can broaden the team’s initial knowledge base and set the
stage for expanding that base as members learn from one another. Historically,
however, the scientific literature has documented repeatedly that teams often fail
to benefit from minority dissent when it is offered (Esser 1998, Janis 1982, Turner
& Pratkanis 1998) or fail to access unique information possessed by members
(Wittenbaum et al. 1999). Thus, it is not surprising that much of the current literature has been devoted to this issue.
Gibson & Vermeulen (2003), in a field study of teams working in the pharmaceutical industry, showed how learning could be accomplished by managing
the team’s composition. Extending prior research by Lau & Murnighan (1998) on
group fault lines, Gibson & Vermeulen argued that diversity in the team’s demographic characteristics is conceptually and empirically distinguishable from the
degree to which there are identifiable subgroups in the team. A four-person team
composed of two women and two men, two African Americans and two Caucasians, and two people from operations and two from marketing is diverse, but
may or may not contain subgroups depending upon whether the differences are
crossed. Thus, if both African Americans are also both women and also both in
marketing, this creates two very strong subgroups in the team, which would not
be the case if one of the African Americans was a man, and one of the men was
in marketing, and one of the marketing representatives was an African American.
Gibson & Vermeulen (2003) showed that unless one controls for the degree of subgroup formation, the level of the team’s diversity does not predict team learning.
Teams learned best when there were a moderate number of weak subgroups.
The importance of avoiding minority opinions was also documented in a study
by Ellis et al. (2003) using a “connecting the dots” paradigm. In this paradigm, no
one team member could learn based solely on his or her own personal experience.
Unlike Gibson & Vermeulen’s (2003) compositional approach, Ellis et al. took
a structural approach to this same problem. Based upon past research on collective induction and the “truth supported wins” models (Laughlin 1999), this study
showed that teams learned best when their resource allocations and task structures
created “role partners” who could replicate, confirm, and support each other’s personal experiences. Structures that created specialized loners failed to learn because
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of the noncommensurate nature of their experiences, and teams structured in terms
of overly broad generalists failed to learn because of information overload. The
presence of weak subgroups seems to afford each team member some degree of
“psychological safety” (Edmondson 1999, Edmondson et al. 2001) when sharing
their experiences or expressing their doubts, and this seems to be essential to promote the level (De Dreu & West 2001) and nature (Lovelace et al. 2001) of group
participation that creates team-level learning.
In terms of composition, Ng & Van Dyne (2001) found that value differences
in terms of collectivism and individualism on the part of both dissenters and the
team as a whole were critical determinants of group dynamics when there are opportunities for minority influence. Teams that were, on average, high on horizontal
collectivism—a value emphasizing interdependence, sociability, and equality of
in-group members—and low on horizontal individualism—a value stressing independence, self-reliance and equality—benefited more from the expression of
minority dissent in their groups relative to other groups. Groups that were high
on vertical collectivism—a value orientation that emphasizes interdependence but
recognizes status inequalities—only obtained benefits from minority dissent when
the dissenter was high in status. With respect to the dissenters themselves, the
results indicated that vertical individualists were least stressed when placed in a
position where they had to espouse a minority viewpoint, and this in turn led to
greater social influence for these individuals. Thus, composition affected team’s
ability to benefit from minority dissent, but ironically, the very people most likely
to express dissent (individualists) were least likely to be influenced by it.
McLeod et al. (1997) revealed a similar irony in a study that examined a more
structural approach to minority dissent. Using the widely employed “hidden profile” paradigm, McLeod et al. found people were more likely to dissent when
interacting in a context that was not face-to-face. Minority dissent, however, was
less likely to have an impact on team members in this condition, relative to face-toface conditions. Groups that encounter a minority dissenter in face-to-face contexts
seem to admire the person’s courage, and in line with norms for politeness, are
more likely to work to incorporate this person’s input into the group’s discussion,
whereas anonymous, electronically submitted dissent tended to be ignored.
In addition to learning from minority members, teams also need to learn from their members under different circumstances, and then use this knowledge to improve performance and expand the
knowledge of other team members. Indeed, although much has been written about
the value of information sharing and group discussion for promoting performance,
two separate recent studies showed the value of learning who is the most knowledgeable member for making decisions based on discussions (Lavery et al. 1999,
Littlepage et al. 1997). The ability of the team to learn from the most knowledgeable
and to perform well is greater when task difficulty is higher (Bonner et al. 2002).
Research that examines how teams or team leaders develop differential weighting systems for aggregating individual member judgments into a single judgment
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for the team can be found under many different headings. The Team Lens Model
(Brehmer & Hagafors 1986), Judge-Advisor Systems (Sniezek & Buckley 1995;
Sniezek & Henry 1989, 1990) and the Multilevel Theory of Team Decision-making
(Hollenbeck et al. 1995; Phillips 2001, 2002) all examined this issue from slightly
different perspectives. A detailed description of all of the research conducted under
this heading is beyond our scope (see Humphrey et al. 2002 for a recent review
of this literature), but the general patterns that emerge from this literature are
worth noting, especially as they relate to team-level learning. Left to their own devices, most teams fail to learn the optimal schemes for integrating diverse opinions
(Humphrey et al. 2002).
Finally, although this section has generally conceptualized team learning as a
beneficial process that organizations might want to support, it needs to be noted
that some of the factors that are known to promote learning and flexibility often
do so at the expense of efficiency. Indeed, research by Bunderson & Sutcliffe
(2003) found an inverted-U relationship between learning orientation and longterm performance in teams, and that the downward slope of the curve comes sooner
for previously high-performing teams relative to teams that have struggled.
All of this suggests the need to balance the team’s need to experiment and grow
with the need to execute and survive, and nowhere is this duality more difficult
to manage than in what some have referred to as “high-reliability organizations”
(HROs). Weick et al. (1999) defined HROs as those that operate in an unforgiving
competitive, social, and political environment that is rich for potential for error, and
where the scale of consequences associated with error precludes learning through
experimentation. This would include operations in nuclear power plants, air traffic
control, naval aircraft carriers, and space shuttle operations. In these contexts, the
team’s first error may be its last, and thus the standard approaches to learning
through experimentation or trial-and-error processes cannot be employed (Weick
et al. 1999).
Weick et al. documented that successful HROs balance the need to learn and
improve with the need for flawless execution by inducing in their members a high
state of mindfulness. They identify five specific processes that organizations use to
induce this state, including (a) a preoccupation with small failures or near misses
that may be diagnostic for larger problems; (b) reluctance to simplify, explain
away, or cover-up near misses, but a tendency instead to reward people for reporting them and studying them; (c) a high degree of sensitivity to operations at
the tactical level, where team members create collective situational awareness via
story-building techniques; (d) resilience, or the ability to bounce back or recover
from small errors via contingency planning and containment systems; and finally
(e) underspecifying structures and operations in order to prevent tight coupling
of systems, thus preventing errors in one component of the system to trigger a
cascading set of errors quickly down the chain. All of these processes are institutionalized by “after-action reviews,” and, although not all organizations may be
classified as HROs, Weick et al. argued that many would be better off in the long
term if they acted as if they were. Indeed, unlike in HROs, teams often never look
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back, thus precluding the opportunity to learn. Too little attention has been paid
to processes that allow some teams to benefit more from their experiences than
others.
FINISHING
Groups and teams in organizational contexts disband for many reasons. The ending may be planned, as is the case for task forces or crews, or unplanned, as in
the collapse due to interpersonal tensions, task failure, or many other reasons including member loss of interest in remaining together (Arrow et al. 2000). Of the
three phases of teams in our framework, however, finishing processes are conspicuous in their absence from the empirical teams literature. This is somewhat
surprising given the multiple theoretical statements emphasizing this phase in the
life of a team. Several stage models of team development have addressed finishing processes, calling the end-stage adjourning (Tuckman & Jensen 1977), decay
(Worchel 1994), or termination (van Steenberg LaFarge 1995). Although other
team models have eschewed the notion of teams progressing predictably through
stages, they also have dealt theoretically with finishing processes, referring to the
phase as completion (Gersick 1988), transition (Marks et al. 2001), and metamorphosis (Arrow et al. 2000). Clearly, because many view the decline and eventual
disbanding of members to be an important phase in the life cycle of teams, much
more empirical work is needed on this final phase.
CONCLUSION
We are left with two general impressions of the recent teams literature, one more
positive than the other. The most striking development is a convergence on common
perspective of teams along with theories and methods to address the complexities
of the perspective. Teams are viewed as complex, adaptive, dynamic systems, and
they are embedded in organizations and contexts and performing tasks over time
(Ilgen 1999). Theories directed at teams/small groups in general (Arrow et al.
2000), adaptive teams (Kozlowski et al. 1999), team process (Marks et al. 2001),
or focused on issues of training (Cannon-Bowers & Salas 1998, DeShon et al.
2004), provide excellent frameworks for addressing team behavior. Methodological and computational developments also are appearing to handle more effectively
the complexities of multilevel problems (e.g., Klein & Kozlowski 2000). In addition, mathematical (Losada 1999) and computational models are being strongly
advocated (Arrow et al. 2000, Hulin & Ilgen 2000) for aiding the understanding of
organizational behavior in teams and other settings. A recent National Research
Council study panel (Pew & Mavor 1998) shows that these models have been extremely helpful in application to military simulations. In many respects, theories
and methods that have recently emerged provide a firm foundation on which to
build into the future.
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The domain of empirical studies, although possessing a number of interesting
and important studies (as we have pointed out in our review), is far less cohesive or
coherent in its entirety than is theory and method. In part, this may be because the
research is more problem-driven than theory-driven. Demands of rapidly changing markets, the need for command and control, stressful military settings, and
the existence of virtual organizations spanning national borders cry for the design
of organizational systems incorporating teams and research to address each specific problem. Problems and the time urgency that often accompanies them direct
attention away from programmatic research directed toward the development of
overarching theories. It also leads to unsystematic sampling of the theory space as
is evidenced by the paucity of work on teams as they decline. It has also led to a
proliferation of processes that often are not very well articulated, as Marks et al.
(2001) noticed in their review of team process where the differentiation between
team process and resulting states of these processes (emergent states) were often
blurred. Finally, although the importance of dynamic conditions experienced over
time are accepted by all, the empirical work is only beginning to consider the
implications of time in research designs. Thus, the empirical research lags behind
the theoretical and methodological work at this time. However, given the strength
of the latter and the level of activity in all domains of the study of teams, we are
optimistic that the next Annual Review of Psychology chapter on teams will see
even greater progress than we witnessed.
ACKNOWLEDGMENTS
We thank the Office of Naval Research (N00014-00–1-0398) for support to prepare
this review and for the many opportunities given to J. R. Hollenbeck, D. R. Ilgen,
and their students to study and participate in many kinds of teams. While we
gratefully acknowledge the support, we also acknowledge that the ideas are ours
and the support does not imply endorsement by the Office of Naval Research.
The Annual Review of Psychology is online at http://psych.annualreviews.org
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