Mismatches between Perceiving and Actually Sharing Temporal Mental Models: Implications for Distributed Teams

Jacqueline Marhefka, Susan Mohammed, Katherine Hamilton, Rachel Tester, Vincent Mancuso, and Michael D. McNeese

CONTENTS

Theoretical Background.........................................................................................161

Team Mental Models.........................................................................................161

Actual and Perceived Sharedness......................................................................162

Hypotheses.............................................................................................................164

Viability.............................................................................................................164

Main Effect...................................................................................................164

Comparative Hypothesis..............................................................................164

Moderated Hypothesis..................................................................................165

Team Performance............................................................................................166

Main Effect...................................................................................................166

Comparative Hypothesis..............................................................................166

Moderated Hypothesis..................................................................................166

Method...................................................................................................................167

Participants........................................................................................................167

NeoCITIES Simulation.....................................................................................167

Procedure...........................................................................................................168

Measures...........................................................................................................169

Results....................................................................................................................170

Descriptive Statistics.........................................................................................170

Data Analysis....................................................................................................170

Tests of Hypotheses...........................................................................................170

Discussion..............................................................................................................176

Implications.......................................................................................................177

Limitations and Future Directions....................................................................178

Conclusion.........................................................................................................179

References..............................................................................................................179

Distributed or virtual teams are becoming increasingly prevalent in occupational areas ranging from legal services to software development to hospital and medical services (Gilson, Maynard, Young, Vartiainen, & Hakonen, 2015; Kimble, 2011). Compared to teams with more face-to-face interaction, distributed teams face unique challenges due to the absence of normally salient visual, auditory, and social team member cues that facilitate positive group dynamics (Kimble, 2011). As a result, virtual team interactions may deteriorate into process loss in which the team fails to live up to its potential (Schmidtke & Cummings, 2017). Due to the lack of opportunity for unspoken knowledge sharing through social and physical cues, there is greater difficulty in processing task information in virtual teams (McLeod, 2013; Rentsch, Delise, Mello, & Staniewicz, 2014) and less open information sharing (Bazarova & Walther, 2009; Mesmer-Magnus, DeChurch, Jimenez-Rodriguez, Wildman, & Shuffler, 2011). The lack of face-to-face interactions may contribute to coordination breakdowns and mistrust (McLeod, 2013). Lack of trust, in turn, may contribute to biases in interpretations and judgments about other members, hampering understanding of team member behavior (Bazarova & Walther, 2009).

How' members “get on the same page” regarding what will be accomplished and how team duties will be managed is a formidable challenge in any team context, but especially in distributed teams. Distributed cognition examines how cognitive systems are organized both between people and with resources in the virtual environment (Hollan, Hutchins, & Kirsh, 2000). Despite agreement that it is important to investigate, research has given minimal attention to how shared cognition develops in virtual teams (Maynard & Gilson, 2014; Schmidtke & Cummings, 2017). As a specific type of shared cognition, we focus on team mental models (TMMs) or the shared, organized understanding of the key elements in a team’s environment (Mohammed, Ferzandi, & Hamilton, 2010). According to Ellwart, Happ, Gurtner, and Rack (2015), it is critical, particularly for virtual teams, to synchronize thinking patterns and expectations to develop a shared TMM. Throughout the chapter, we focus on sharedness or similarity as the primary property of TMMs (Mohammed et al., 2010). Whereas TMMs describe similarity on taskwork, teamwork, or “time-work” (Mohammed, Hamilton, Tesler, Mancuso, & McNeese, 2015), shared situational awareness addresses members’ shared understanding of the current situation (Wellens, 1993).

In the early 1990s, the concept of TMMs was developed to capture implicit coordination within a team (Cannon-Bowers, Salas, & Converse, 1993; Klimoski & Mohammed, 1994). Members with high TMM similarity are able to anticipate each other’s behaviors and needs (Cannon-Bowers et al., 1993). Over two decades of conceptual, measurement, and empirical research has solidified the TMM construct as a unique and impactful form of team cognition (Mohammed et al., 2010). TMMs are recognized as an important contributor of team effectiveness

(Mohammed et al., 2010) due to their impact on team processes such as coordination (Salas, Sims, & Burke, 2005) and outcomes including performance (DeChurch & Mesmer-Magnus, 2010a, 2010b). Despite substantive progress in TMM research, several research needs continue to be identified, including the awareness of sharing among team members (Mohammed et al., 2010).

Specifically, what happens w'hen team members think they are in agreement but are not in actuality? Discrepancies between perceptions and reality can exist in any team, but particularly for distributed teams. Due to the difficulty in sensing team members’ contexts and motives (Bazarova & Walther, 2009) as well as the lack of visual and social cues (Rentsch et al., 2014), it is likely that virtual teams will struggle to accurately detect perceived and actual TMM similarity. The misperceptions that result may prove detrimental to performance and continued member interactions. In response to this special challenge in distributed teams, we examined the relationship between perceived and actual TMM similarity on team performance and viability (willingness of team members to work together in the future). We focused specifically on temporal TMMs, common views held by the team about the time-related aspects of performing collective tasks (Mohammed et al., 2015).

Theoretically, this study helps to resolve a long-standing debate in the TMM literature regarding the role of perceptions of similarity (Mohammed et al., 2010). Because most TMM research has examined only actual sharedness, little is known about mismatches between perceived and actual TMM similarity (Rentsch, Small, & Hanges, 2008). Empirically, we simultaneously assess actual and perceived TMM similarity, whereas previous studies have examined either, but not both. Practically, this research could help to diagnose teams that think they are in sync, but are not in actuality, paving the way for targeted and tailored training.

THEORETICAL BACKGROUND

Team Mental Models

TMMs are a specific form of team cognition, a broader concept describing how knowledge is gathered and held within a team. TMM similarity describes how convergent or consistent team members’ mental models are with each other (Rentsch et al., 2008). TMMs diverge from other forms of team cognition in two fundamental ways.

First, TMMs subsume greater breadth of content, including taskwork (what the team must do in order to complete goals), teamwork (who team members interact with and how they work together collectively), and more recently, “timework” (when members interact with each other) (e.g., Cooke, Kiekel, Helm, & Usability, 2001; Mohammed et al., 2015). In contrast, other forms of team cognition tend to focus on only one category of content, such as taskwork (transactive memory systems) or teamwork (group learning) (Mohammed et al., 2010).

Second, TMM measurement requires that both content and structure be assessed. Structure refers to the relationships between concepts in team members’ heads

(Mohammed et al., 2010). In contrast, other types of team cognition such as transactive memory (Lewis, 2003) or group learning (Edmondson, 1999) capture content only using Likert scales. Alternatively, TMMs assess structure via techniques such as concept mapping, in which participants determine the placement of concepts hierarchically (Marks, Sabella, Burke, & Zaccaro, 2002).

A meta-analysis concluded that TMM similarity is an important contributor to team performance outcomes such as work quality, volume, efficiency, and timeliness, above and beyond other behavioral or motivational states and team processes (DeChurch & Mesmer-Magnus, 2010a). TMMs also positively predict implicit team coordination (Rico, Sanchez-Manzanares, Gil, & Gibson, 2008) and adaptation (Burke, Stagl, Salas, Pierce, & Kendall, 2006).

Most of the TMM literature has focused on taskwork and teamwork content, but increasing attention is being given to “timework,” or temporal TMMs. A temporal TMM is defined as “agreement among group members concerning deadlines for task completion, the pacing or speed of activities, and the sequencing of tasks” (Mohammed et al., 2015, p. 696). Deadlines indicate the specific time by which a task should be completed (Blount & Janicik, 2002). Pacing refers to how team members distribute effort towards completing a task over time (Blount & Janicik, 2002). Sequencing describes when steps must be completed in a specific order. In summary, team members must be on the same page regarding deadlines and pacing, as well as the ordering of subsequent steps to have high temporal TMM similarity (Mohammed et al., 2015). Initial studies found direct or conditional positive effects for temporal TMMs on team performance (Mohammed et al., 2015; Santos, Uitdewilligen, & Passos, 2015; Santos, Passos, Uitdewilligen, & Niibold, 2016). Given that the extant research on temporal TMMs is nascent, but promising, we focus on temporal TMMs in the current research.

Actual and Perceived Sharedness

Two forms of collective team cognition are structured and perceptual (DeChurch & Mesmer-Magnus, 2010a). Structured cognition captures the actual organization, patterns, and arrangement of the team’s knowledge, as measured by concept maps or similarity ratings (Mohammed et al., 2010). Perceptual cognition consists of general attitudes, beliefs, values, and expectations of team members. To measure the team’s awareness of their TMM similarity, team members respond to Likert scale items addressing how similar they feel components of the TMM are or the extent to which the team is on the same page (Rentsch et al., 2008). A sample item assessing perceived temporal cognition is “team members had similar thoughts about the best way to use the time available” (Gevers, Rutte, & van Eerde, 2006). Because of the measurement emphasis on structure and objectively comparing whether team members’ mental maps are similar, perceptions of sharedness have received little attention in the TMM literature.

Disagreement remains regarding whether demonstrating actual similarity is enough to qualify as a shared mental model, or whether team members also have to

Actual

Perceived

Not In Sync

In Sync

In Sync

False Positive Viability High Performance Low

True Positive

Viability Higher

Performance Higher

Not In Sync

True Negative Viability Lower Performance Lower

False Negative Viability Low Performance High

FIGURE 7.1 The interactive effects of perceived and actual temporal TMM similarity on viability.

Note: High actual temporal TMM slope is significant (p < .001) while low actual temporal TMM slope is insignificant (p > .05).

perceive that they are in agreement (Mohammed et al., 2010). For example, Klimoski and Mohammed (1994) indicated that one component of a TMM is its reflection of internalized perceptions and assumptions, meaning that teams must have an understanding that they are on the same page. Conversely, Rentsch, Delise, and Hutchison (2009) argue that a team may have higher similarity of knowledge organization, qualifying as a TMM, but be ignorant of consensus. Unfortunately, it is difficult to test these competing views when few studies examine both the actual and the perceived sharedness concurrently.

Although our study variables are continuous, it is useful to note that there are four resulting categories when conceptualizing perceived and actual temporal TMM sharedness as a 2 x 2 matrix, as seen in Figure 7.1.

One category is a true positive in which a team believes it is in sync and is in actuality, and the opposite is a true negative in which a team does not perceive being in sync and is not in reality. A false positive occurs when a team perceives that it is in sync, but is not in actuality. Finally, a false negative occurs when a team perceives that it is not in sync, but actually is. Mismatches between perceptions of whether teams are in or out of sync may have differential influences on team outcomes.

The TMM literature is deficient in research examining the relationship between actual and perceived TMM similarity (Mohammed et al., 2010), and this deficiency is particularly salient in a distributed cognition context. Due to the additional difficulty sensing team members’ contexts and motives (Bazarova & Walther, 2009) as well as the lack of visual and social cues (Rentsch et al., 2014), it is likely that virtual teams will struggle with temporal misperceptions and mismatches between actual and perceived TMM similarity. In addition, discrepancies may be particularly heightened for temporal TMMs, as time may be discussed less explicitly than what must be done or how it should be done in order to perform a task (Mohammed et al., 2015).

HYPOTHESES

As delineated by Hackman (1987), two forms of effectiveness examined in this study were team viability and performance. Each will be discussed below.

Viability

Main Effect

In contrast to objectively measured team performance, viability is a perceptual outcome assessing whether team members believe that they should continue to interact together in the future as a team. Viability often derives from optimistic emotions in combination with positive team member interactions (Costa, Passos, & Barata, 2015). Beyond these affective predictors, it is expected that emergent states such as TMM similarity would likely also influence viability.

When there is synchrony between team members, higher viability is expected because team members feel comfortable and compatible with one another (DePaulo & Bell, 1990). Perceptions of synchrony, through unconscious mimicry (the tendency to adopt mannerisms of another without intent), results in increased reports of rapport and liking (Lakin, Jefferis, Cheng, & Chartrand, 2003). As interpersonal synchrony results in higher perceptions of smooth interactions and rapport, team members will feel understood by other team members and other team members will feel understood by each other (DePaulo & Bell, 1990).

Blount and Janicik (2002) noted that people have an “in-sync preference,” which refers to a consistent desire to be synchronous and cohesive with others. Whereas an “in-sync preference” results in favorable reactions through feeling attuned with team members, an “out of sync effect” describes the negative emotions resulting from feeling uncoordinated with others. Not only will positive feelings not occur when team members are not synchronous, but negative emotions will arise as an outcome. Such negative perceptions may decrease viability within teams (Balkundi, Barsness, & Michael, 2009). In contrast, as team members perceive each other to be in sync, they are more likely to experience rapport, liking, and smooth interactions, increasing the likelihood that they would want to work together in the future. Indeed, Rentsch and Klimoski (2001) found that agreement on teamwork TMMs was positively related to team viability. Extending this finding to temporal TMMs, we expect the following:

Hypothesis 1: Perceived temporal TMM similarity will have a positive effect on team viability.

Comparative Hypothesis

The bandwidth-fidelity argument describes the importance of measuring specific or narrow criterion with specific or narrow measures, and general or broad criterion with general or broad measures. Judge and Kammeyer-Mueller (2012) note that theoretically, as well as empirically, specific predictors are more foretelling of narrow' criteria, and general predictors are more favored by broad criteria. Analogous to the bandwddth-fidelity argument, we expected that perceived TMMs are more likely to positively affect perceptual outcomes. That is, compared to actual temporal TMMs, perceived temporal TMMs would be more likely to predict viability as a perceptual criterion.

In addition to the alignment between perceptual predictors and perceptual outcomes, there is a close conceptual match between perceived temporal TMMs and viability. The team’s subjective perception of having a common understanding of deadlines, ordering, and pacing is likely to positively influence their desire to work together on future projects. Because the actual temporal TMM similarity is more directly related to the objective performance scores (DeChurch & Mesmer-Magnus, 2010a, 2010b), it is anticipated that the actual similarity will be less positively related to viability than the perceived temporal TMM similarity.

Hypothesis 2: Compared to actual temporal TMM similarity, perceived temporal TMM similarity will have a more positive effect on team viability.

Moderated Hypothesis

In addition to perceived temporal TMM similarity predicting viability, it is also expected that actual temporal TMM similarity will moderate this relationship. When actual temporal TMM similarity is higher, the positive relationship between the perceived temporal TMM similarity and viability is expected to increase. Team members can be more confident that they will continue to work well together in the future when actually being in sync supports perceptions of being in sync. Greater actual temporal TMM sharedness allows the team to understand and anticipate actions more successfully (Gevers et al., 2006), enhancing in sync sentiments and subsequent rapport and fondness.

However, when actual temporal TMM similarity is lower, the relationship between perceived temporal TMM similarity and viability is expected to be less positive. When teams have lower temporal TMM sharedness, confusion may result, as team actions are less likely to be foreseeable (Balkundi et al., 2009). As hints are received that team members are not on the same temporal page and tasks are being completed in an unexpected order, perceptions of confusion and uncertainty are confirmed. The realization that members are not actually in sync may discourage members from interacting or confronting these underlying conflicts, creating doubt as to whether team members will desire to work together in the future. Thus, lower actual temporal TMM similarity would strengthen the relationship of lower perceived temporal TMM similarity and lower viability.

Taking a different perspective, affective-cognitive consistency impacts the strength of job attitudes, such that when affective-cognitive consistency is low there is less strength in the relationship (Schleicher, Watt, & Greguras, 2004). Following this logic, if the actual temporal TMM (analogous to the cognitive component of the attitude) is not consistent or in sync with the perceptual (analogous to the affective component of the attitude), the relationship between actual temporal TMM similarity and viability will not be as positive as when they are consistent. Therefore, in addition to a main effect of perceived temporal TMM similarity on viability, considering the interaction between perceived and actual temporal TMM similarity allows for a more sophisticated understanding. Overall, particularly in virtual contexts, teams that believe that they are in sync, and in actuality really are in sync, will have higher viability than teams that believe that they are in sync but actually are not.

Hypothesis 3: The relationship between perceived temporal TMM similarity and viability is moderated by actual temporal TMM similarity, such that the relationship will be more positive when actual temporal TMM similarity is higher than lower.

Team Performance

Main Effect

Team performance is the most studied effectiveness outcome in the team literature (Mohammed et al., 2010). Across a variety of performance settings and outcomes, TMM similarity holds a positive relationship with team performance (Cooke et al., 2001; Edwards, Day, Arthur, & Bell, 2006; Ellis, 2006; Mathieu, Heffner, Goodwin, Cannon-Bowers, & Salas, 2005; Rentsch & Klimoski, 2001). In addition, two meta-analyses have confirmed that TMMs positively predict team performance (DeChurch & Mesmer-Magnus, 2010a, 2010b). This association is particularly true for interdependent tasks, which require additional levels of coordination of member input and effort (Leroy, Shipp, Blount. & Licht, 2015; McGrath, 1991). Temporal TMMs have also been found to be positively related to team performance (e.g., Mohammed et al., 2015). Expecting to replicate these findings, we predict:

Hypothesis 4: Actual temporal TMM similarity will have a positive effect on team performance.

Comparative Hypothesis

Drawing again from the bandwidth-fidelity argument (Judge & Kammeyer-Mueller, 2012), we suggest that actual temporal TMM similarity will relate more to performance than the perceived similarity. Compared to perceived temporal TMMs, we expect that actual temporal TMMs will be more likely to predict performance as an objective criterion. Actual temporal TMM similarity as measured through objective methods is positively related to performance outcomes in a variety of settings (DeChurch & Mesmer-Magnus, 2010a, 2010b, Mohammed et al., 2015). However, as a more subjective measure, perceived temporal TMM similarity is likely to be less related to objective performance. Perceptions are not necessarily indicative of actual similarity, and as such would not hold as positive of a relationship with performance as actual temporal TMM similarity.

Hypothesis 5: Compared to perceived temporal TMM similarity, actual temporal TMM similarity will have a more positive effect on team performance.

Moderated Hypothesis

Although actual temporal TMM similarity is anticipated to positively affect team performance, considering perceived temporal TMM similarity as a moderator is expected to affect the relationship between actually being in sync and team performance. When perceived temporal TMM similarity is higher, the relationship between actual temporal TMM similarity and team performance is expected to be more positive. When teams interpret that they are performing tasks in the expected order or working at the anticipated pace, reports of rapport, understanding, and communication increase (DePaulo & Bell, 1990; Lakin et al., 2003). This leads to better coordination of team actions, ultimately positively impacting performance outcomes (Blickensderfer, Cannon-Bowers, & Salas, 1998; Cannon-Bowers, Tannenbaum, Salas, & Volpe, 1995). In other words, this increase in communication and liking encourages discussion, including of temporal elements, resulting in higher performance by leveraging the actual temporal TMM similarity.

When teams do not perceive that they are in sync, the relationship between the actual temporal TMM similarity and performance will be less positive. Although teams may have higher actual temporal TMM sharedness, if teams perceive lower similarity, they are less likely to feel encouraged to communicate more frequently with each other to increase performance outcomes. That is, it is the perception of being out of sync and the desire to get back into sync that is likely to prompt communication to become in sync, thereby improving performance.

Just as high affective-cognitive consistency results in a more positive relationship between attitudes and performance, high levels of consistency between the actual and perceived temporal TMM sharedness will result in a more positive relationship with team performance when sharedness is high than if the perceived temporal TMM differs from the actual state.

Hypothesis 6: The relationship between actual temporal TMM similarity and performance is moderated by perceived temporal TMM similarity, such that the relationship will be more positive when perceived temporal TMM similarity is higher than lower.

METHOD

Participants

The study consisted of 546 undergraduate participants from a large mid-Atlantic university, who were randomly assigned to teams consisting of three members (resulting in 182 teams). The mean age of participants was 20.15 years (SD = 1.01), with 69% being Caucasian and 57% being female. Participants were primarily in their first, second, or third year of attending the university. Course credit or extra credit was received in return for participation.

NeoCITIES Simulation

Students participated in NeoCITIES, an emergency crisis management team computer simulation in which participants had to respond to a range of disaster situations (McNeese et al., 2005). Each team member was randomly assigned to one of three roles: fire/emergency medical services (EMS), police, or hazardous materials

(hazmat). Each role had several resources to allocate. For instance, fire/EMS had trucks, ambulances, and fire investigators to utilize. Emergency situations of varying types and levels arose, and participants were tasked with coordinating with the other team members to determine the severity of the event, sending the appropriate type and amount of resources at the correct time, and determining what resources other team members needed to address the situation. Resources were limited, and sending excess resources to a minor event could cause a delay in response to a more serious emergency due to the time required to recall resources (Hellar & McNeese, 2010). Participants were seated at a personal computer and separated by dividers. They communicated exclusively via instant messaging in a chat box.

The environment in the simulation changed depending on the students’ responses, meaning that if a minor situation was not dealt with quickly, it could escalate into a larger issue. As each member received unique information, it was critical that the team communicate in order to successfully solve interdependent tasks. This hidden profile situation, in which one team member held specific knowledge about how a task should be handled, increased the interdependence between team members.

There were several advantages to using the NeoCITIES simulation in this study. The emergency crisis setting allowed for a realistic and complex domain requiring teams to coordinate and work interdependently in a virtual context. Furthermore, the simulation was designed to study team cognition and team performance (McNeese et al., 2005), with dynamic and uncertain situations. Team members also held different roles, so cooperation and timeliness of information sharing as well as decision making were essential elements for success.

Procedure

The current study was part of a larger data collection supported by the Office of Naval Research (Grant Number N000140810887; Mohammed, Hamilton, Sanchez-Manzanares, & Rico, 2017). The larger data collection included three manipulated variables: individual reflexivity (reflecting individually on one’s performance), group reflexivity (reflecting as a group on the team’s performance), and storytelling (conveying audio and visual information about the need for team collaboration and timing in an engaging manner using the principles of narrative). Although not of substantive interest in this study, these interventions were examined for their potential influences on team cognition (see Mohammed et al., 2017 for an overview) and controlled for in analyses.

Participants were randomly assigned to their role on the team (fire, police, hazmat) when they entered the lab. After completing an electronic survey measuring demographic information, participants were instructed on how to play the NeoCITIES simulation. Participants practiced individually for five minutes to understand the basic simulation elements and then practiced for five more minutes with other team members on a more complex, interdependent scenario. After reviewing how they performed on the training scenarios and the solutions to each event, they played two performance simulation rounds lasting 15 minutes each. The storytelling, individual reflectivity, and team reflexivity manipulations occurred following the first performance round in the order listed. After each round, teams were given feedback on how well they performed together as a team and completed an online survey, including perceived temporal TMMs, actual TMMs, and viability. Throughout this paper, measures completed after the first performance round will be referred to as Time 1 and measures completed after the second performance round will be referred to as Time 2. The total study lasted about two and a half hours.

Measures

Perceived temporal TMM similarity (Time 1 a = .86, Time 2 a = .90) was collected through responses to six survey items. Items were patterned after Gevers and colleagues (2006) and adapted to the NeoCITIES simulation to measure perceptions of deadlines, pacing, and sequencing. Sample items included, “In our team, we had the same opinion about when to arrive at certain events” and “In our team, we were on the same page regarding the deadline in which multiple units needed to arrive at events.” Aggregation to the team level was justified at Time 2 (ICC(l) = .23, ICC(2) = .57, mean rwg = .90). Although there is less justification at Time 1 (ICC(l) = .05, ICC(2) = .14, mean rwg = .94), it is included in analyses for a more comprehensive model but of less interest.

Actual temporal TMM similarity was measured through a popular TMM measurement tool called concept mapping (Marks, Zaccaro, & Mathieu, 2000) at Times 1 and 2. Participants individually filled in three boxes (one for each role: fire, police, hazmat) indicating the sequence of the units for a given event, meaning which role should respond first, second, then third (Mohammed et al., 2015). For each dyad, one point was awarded for each shared link, and the number of shared links across the three dyads was summed to yield a team score. Higher scores indicated more shared responses (Mohammed et al., 2015).

Team viability (a = .86) was collected through four survey items derived from Tekleab, Quigley, and Tesluk (2009). After the second performance round, participants indicated their level of agreement from 1 (strongly disagree) to 5 (strongly agree) for each of the items. A sample item included “I would be happy to work with the team members on other projects in the future.” Aggregation to the team-level was justified (ICC(l) = .25, ICC(2) = .50, mean rwg = .88).

Team performance was measured objectively via the NeoCITIES simulation at Time 2. Because temporality is of particular interest to this study, timeliness in completing interdependent tasks was used as the performance measure. The NeoCITIES simulation calculated the average duration in seconds it took team members to complete tasks, and this value was inverted so that the average duration represented timeliness in inverted seconds (shorter average duration parallels higher timeliness; D’lnnocenzo, Mathieu, & Kukenberger, 2016; Kellermanns, Walter, Lechner, & Floyd, 2005). As NeoCITIES is an emergency crisis management simulation in which a speedy response time is more ideal, higher timeliness corresponds to better team performance.

Controls: Several variables that are potentially related to TMMs and performance were controlled for in this study. Manipulations of individual reflexivity, group reflexivity, and storytelling were included as controls. As cognitive ability is positively predictive of team performance (Bell, 2007), mean team GPA was controlled for. The percentage of females on the team was also a control variable because gender composition affects performance (Baugh & Graen, 1997). Previous experience has been found to be a positive predictor of TMMs (Rentsch & Klimoski, 2001), so virtual experience (self-reported experience in a virtual environment) was controlled for. To consider the possible performance advantage that may result from previous exposure to emergency situations (e.g., prior EMT training), knowledge of emergency response protocols was also included as a control variable.

RESULTS

Descriptive Statistics

As shown in Table 7.1, actual temporal TMM similarity at Time 1 was positively related to actual similarity at Time 2 (r = .20, p < .01).

Similarly, perceived temporal TMM similarity at Time 1 was positively related to perceived similarity at Time 2 (r = .32 p < .01). As predicted, actual temporal TMM similarity at Time 2 was positively related to timeliness (r = .19, p < .01). However, this relationship was not significant for actual temporal TMM similarity at Time 1. Interestingly, perceived temporal TMM similarity at Time 2 was also correlated with timeliness (r = -.36, p < .01), but negatively. This relationship was not significant for perceived temporal TMM similarity at Time 1. As expected, perceived temporal TMM similarity was positively related to viability at Time 1 (r = .38, p < .01) and 2 (r = .51, p < .01). Interestingly, higher timeliness was associated with lower viability (r = -.30, p < .01).

Data Analysis

Hierarchical regression was used to test the hypotheses at the team level. When team performance was the dependent variable, all control variables listed above were entered in Step 1. For viability as the dependent variable, the controls excluded mean GPA and knowledge of emergency response protocols because there was not compelling rationale or prior findings to include them. In Step 2, actual temporal TMM similarity at Time 1 and Time 2 were entered. Step 3 added the perceived temporal TMM similarity at Times 1 and 2. The interaction between perceived temporal TMM similarity at Time 1 and actual temporal TMM similarity at Time 1 and Time 2 were entered in Steps 4 and 5, respectively. The parallel interactions with perceived temporal TMM similarity at Time 2 were entered in Steps 6 and 7.

Tests of Hypotheses

As shown in Table 7.2, perceived temporal TMM similarity significantly and positively influenced team viability at Times 1 and 2 (¡3 = .23, p < .01; [3 = .43, p < .01), lending support to Hypothesis 1.

Perceived temporal TMM similarity explained an additional 29% of unique variance in viability (A/?2 = 0.29, p < .01) beyond controls and actual temporal TMM similarity.

According to Hypothesis 2, perceived temporal TMM similarity would have a more positive effect on viability than actual temporal TMM similarity. As predicted, perceived temporal TMM similarity at Time 1 had a stronger positive relationship with viability (r = 0.38, p < .01) than actual temporal TMM similarity at Time 1 (r = -.10, p > .05) and Time 2 (r = -.05, p > .05). These correlations were significantly

TABLE 7.1

Descriptive Statistics and Correlations

M(SD)

1

2

3

4

5

6

7

8

9

10

11

12

Controls

I. Group reflexivity condition”

,34(.95)

1.0

2. Individual reflexivity condition“

,32(,95)

-.51**

1.0

3. Storytelling condition“

-.05(1.00)

.04

.01

1.0

4. Team percent of females'*

0.58(32)

.13

-.03

.18*

1.0

5. Mean team GPA

3.23(38)

-.03

.03

-.12

.14

1.0

6. Experience in virtual environment

1.89(36)

.18*

<.01

-.08

-.16*

.06

1.0

7. Knowledge of emergency response protocols

1.66(.46)

.01

<.01

.05

-.11

-.14

.11

1.0

Actual Temporal Similarity

8. Actual temporal TMM similarity Tl

.77(31)

.09

-.10

.05

.21**

.08

-.08

-.04

1.0

9. Actual temporal TMM similarity T2

.90(32)

.18*

-.14

-.01

-.03

<01

.06

.02

.20**

1.0

Perceived Temporal Similarity

10. Perceived temporal similarity Tl

3.08G43)

.01

.06

.06

-.26**

-.05

.12

.00

-.15*

-.01

1.0

ll. Perceived temporal similarity T2

3.78G46)

.12

-.08

-.03

-.07

.10

.08

-.01

.02

.01

.32**

1.0

Outcomes

12. Timeliness

-57.55(11.94)

-.05

.10

.13

.15*

.02

.06

.04

.04

.19**

-.09

-.36**

1.0

13. Viability

3.86(35)

.12

-.03

.03

-.08

-.03

.09

-.07

-.10

-.05

.38**

.51**

-.30**

Mismatches between Perceiving and Sharing

Note: N= 182 teams.

“ Contrast coded variable: control = -I; Group reflexivity/individual reflexivity/storytelling = I

b Team gender composition of team, percent of females ranging from 0 (all males) to 1.00 (all females) *p < .05, two-tailed; “/>< ()I. two-tailed

TABLE 7.2

Hierarchical Regression Analyses Testing the Effect of Actual and Perceived Temporal TMM Similarity on Viability

Step 1

Step 2

Step 3

Step 4

Step 5

Step 6

Step 7

F

1.01

1.05

9.43*

*

8.44**

7.64**

7.50**

6.90**

R2

.03

.04

.33**

.33**

.33**

.35**

.35**

ER2

.03

.01

.29**

.00

.00

.02*

.00

Variable

b

SE

/3

b

SE

/3

b

SE

/3

b

SE

/3

b SE

/3

b

SE

/3

b

SE

/3

Step 1: Controls

Individual Reflexivity Condition

.02

.05

.03

.01

.05

.02

.02

.04

.01

.02

.04

.02

.01 .04

.02

.01

.04

.02

.01

.04

.02

Group Reflexivity Condition

.08

.05

.13

.09

.05

.15

.05

.04

.08

.05

.05

.08

.05 .05

.08

.05

.05

.08

.05

.05

.08

Storytelling Condition

.02

.04

.04

.02

.04

.04

.01

.04

.02

.02

.04

.03

.02 .04

.03

.02

.04

.03

.02

.04

.03

Gender Composition

-.16

.13

-.09

-.14

.14

-.08

.02

.12

.01

.03

.12

.02

.03 .12

.02

.03

.12

.02

.03

.12

.02

Experience in a Virtual Environment

.05

.08

.06

.05

.08

.05

.02

.07

.02

.02

.07

.02

.02 .07

.02

.02

.07

.02

.02

.07

.02

Step 2: Actual Similarity

Actual Temporal TMM Similarity T1

-.14

.14

-.08

-.14

.12

-.08

-.10

.12

-.06

-.13 .12

-.06

-.11

.12

-.06

-.11

.12

-.06

Actual Temporal TMM Similarity T2

-.11

.13

-.07

-.10

.11

-.06

-.11

.11

-.07

-.10 .11

-.07

-.11

.11

-.07

-.10

.11

-.07

Step 3: Perceived Similarity

Perceived Temporal TMM Similarity T1

.30

.09

.23**

.30

.09

.23**

.30 .09

.23**

.30

.09

.23**

.30

.09

.23**

Perceived Temporal TMM Similarity T2

.52

.08

.43**

.51

.08

.43**

.52 .08

.43**

.52

.08

.43**

.52

.08

.43**

Step 4: Actual T1 x Perceived T1

.03

.28

.01

.03 .28

.01

-.14

.29

-.03

-.14

.29

-.03

Step 5: Actual T2 x Perceived T1

.06 .27

.01

.03

.26

.01

.07

.26

.01

Step 6: Actual Tl x Perceived T2

.49

.23

.14*

.50

.23

.14*

Step 7: Actual T2 x Perceived T2

-.10

.30

-.02

172 Foundations and Theoretical Perspectives of Distributed Team Cognition

Note: N = 182 teams *p < .05, **p < .01

different at both Times 1 and 2, respectively (Z = 4.35, p < .01; Z = 4.16, p < .01; Meng, Rosenthal, & Rubin, 1992). Similarly, perceived temporal TMM similarity at Time 2 had a stronger positive relationship with viability (r = 0.51, p < .01) than actual temporal TMM similarity at Times 1 and 2. These correlations were also significantly different at both Times 1 and 2 (Z = -6.13, p < .01; Z = -5.65, p < .01), supporting Hypothesis 2.

Hypothesis 3 predicted that the relationship between perceived temporal TMM similarity and viability would be moderated by actual temporal TMM similarity, such that the relationship will be more positive when actual temporal TMM similarity is higher than lower. As shown in Table 7.2, actual temporal TMM similarity at Time 1 significantly moderated the effect of perceived similarity (at Time 2) on viability (0 = .14, p < .05). The interaction explained an additional 2% of unique variance in viability (AT?2 = 0.02, p < .05) beyond controls and main effects. As recommended by Aiken, West, and Reno (1991), the individual regression slopes were graphed. Figure 7.2 shows that the slope of teams with high actual temporal TMM similarity portrayed a significant, positive relationship (i = 4.37, p < .001).

Meanwhile, the positive relationship of teams with low actual similarity was insignificant (t = .59, p > .05). When perceptions of similarity were high, teams with high actual similarity trended in the direction of higher viability than those with low actual similarity, but not significantly so (i = .46, p > .05). However, when perceptions of similarity were low, ratings of viability were lower when teams had high actual similarity than when teams had low actual similarity (i = -2.43, p< .05). The interaction between perceived (at Time 2) and actual temporal TMM similarity at Time 2 on viability was not significant, nor were the interactions between actual (Time 1 or 2) and perceived at Time 1. This pattern of results lends support to Hypothesis 3 only for actual similarity at Time 1 and perceived similarity at Time 2.

Regarding Hypothesis 4 as seen in Table 7.3, actual similarity at Time 1 did not significantly relate to timeliness (3 = -.01, p > .05).

  • —♦— Low Actual TMM
  • —■— High Actual TMM

FIGURE 7.2 The interactive effects of perceived and actual temporal TMM similarity on viability.

Note: High actual temporal TMM slope is significant (p < .001) while low actual temporal TMM slope is insignificant (p > .05).

TABLE 7.3

Hierarchical Regression Analyses Testing the Effect of Actual and Perceived Temporal TMM Similarity on Performance

Step 1

Step 2

Step3

Step 4

StepS

Step 6

Step 7

F

1.47

2.19»

4.28**

4.26»»

3.95**

3.65**

3.81**

R2

.06

.10*

.22**

.23**

.23**

.23**

.26**

.06

.05*

.11**

.02

.00

.00

.02*

Variable

h

SE

0

h

SE

0

h

SE

0

h

SE

0

h

SE

0

h

SE

0

h

SE

0

Step 1: Controls

Individual Reflexivity Condition

.87

1.09

.07

1.04

1.07

.08

.91

1.00

.07

1.03

1.00

.08

1.02

1.00

.08

1.02

1.00

.08

1.18

1.00

.09

Group Reflexivity Condition

-.82

1.13

-.07

-1.22

1.11

-.10

-.70

1.05

-.06

-.76

1.04

-.06

-.81

1.05

-.06

-.80

1.05

-.06

-.49

1.05

-.04

Storytelling Condition

1.23

.91

.10

1.24

.89

.10

1.18

.84

.10

1.12

.84

.10

1.18

.84

.10

1.19

.85

.10

1.18

.84

.11

Gender Composition

6.19

2.93

.17*

6.65

2.92

.18*

5.79

2.84

.16»

5.85

2.82

.16*

5.83

2.82

.16*

5.84

2.83

.16*

5.77

2.80

.15*

Experience in a Virtual Environment

2.14

1.65

.10

2.00

1.62

.09

2.23

1.53

.11

201

1.52

.10

2.06

1.52

.10

2.07

1.53

.10

2.58

1.53

.12

Mean Team GPA

-1.68

3.21

-.04

-1.76

3.15

-.04

-.08

2.98

-.01

-.29

2.96

-.01

-.25

2.97

-.01

-.19

2.99

-.01

-.26

2.96

-.01

Knowledge of Emergency Response

.82

1.95

.03

.77

1.91

.03

.78

1.80

.03

.89

1.78

.03

.97

1.79

.04

.97

1.80

.04

1.00

1.78

.04

Step 2: Actual Similarity

Actual Temporal TMM Similarity T1

-.57

2.91

-.02

-.06

2.75

-.01

-.89

2.77

-.02

-1.04

2.78

-.03

-.99

2.80

-.03

-.97

2.77

-.03

Actual Temporal TMM Similarity T2

8.31

2.80

.22**

8.00

2.63

.22**

8.67

2.64

.23**

8.74

2.64

.24**

8.71

2.65

.23**

8.11

2.64

.22**

Step 3: Perceived Similarity

Received Temporal TMM Similarity TI

1.29

2.12

.05

1.58

2.11

.06

1.54

2.11

.06

1.54

2.12

.06

1.64

209

.06

Rjrceiwd Temporal TMM Similarity T2

-9.30

1.91

-.36**

-9.13

1.90

—.35**

-9.16

1.90

-.35**

-9.16

1.91

—.35**

-10.23

1.95

_ 39**

Step 4: Actual T1 x Perceived T1

-12.18

6.56

-.13

-12.27

6.57

-.13

-12.67

6.85

-.14

-12.41

678

-.13

Step 5: Actual T2 x Perceived T1

3.84

6.21

.04

3.78

6.23

.04

-2.80

6.84

-.03

Step 6: Actual T1 x Perceived T2

1.20

5.58

.02

-.47

5.57

-.01

Step 7: Actual T2 x Perceived T2

15.27

6.90

.18*

Note: N= 182 teams.

*pc.O5, **p<.01

Foundations and Theoretical Perspectives of Distributed Team Cognition

However, actual similarity at Time 2 was associated with increased timeliness (3 = .20, p < .01). The actual temporal TMM similarity at Times 1 and 2 explained a significant 5% of unique additional variance in the timeliness beyond controls and perceived similarity (A/?2 = 0.05, p < .01). Hypothesis 4 was supported for actual temporal TMM similarity measured at Time 2, but not at Time 1.

Hypothesis 5 stated that actual temporal TMM similarity would have a stronger positive relationship with performance than perceived temporal TMM similarity. Although actual temporal TMM similarity had a positive relationship with timeliness at Time 2 as expected (r = 0.19, p < .01), the correlation magnitude was stronger for perceived temporal TMM similarity at Time 2 and in the opposite direction than predicted (r = -36, p < .01; Z = -5.30, p < .01). There was no significant relationship between actual or perceived temporal TMM similarity at Time 1 with timeliness. Hypothesis 5 was not supported.

Hypothesis 6 predicted that perceived temporal TMM similarity would moderate the relationship between actual temporal TMM similarity and performance, such that the relationship would be more positive when perceived temporal TMM similarity is higher than lower. Perceived similarity at Time 2 significantly moderated the effect of actual similarity at Time 2 on timeliness (3 = .18, p < .05). The interaction explained an additional 2% unique variance in performance (AT?2 = 0.02, p < .05) beyond controls and main effects. A graph of the interaction (see Figure 7.3) demonstrated that the slope of teams with higher perceived temporal TMM similarity portrayed a significant, positive relationship (i = 3.31, p = .001) with timeliness, as expected.

Meanwhile, the positive relationship of teams with low perceived similarity and timeliness was insignificant (i = -.95, p > .05). When teams had high actual

Low Actual TMM High Actual TMM

  • —♦— Low Perceived TMM
  • —■—High Perceived TMM

i-60 a 8 "-65 8 u V

a-70

5-75 s s

f“-80

FIGURE 7.3 The interactive effects of actual and perceived temporal TMM similarity on performance.

Note: High perceived temporal TMM slope is significant (/? < .01) while low perceived temporal TMM slope is insignificant (p > .05).

similarity, those with high perceived similarity were slightly less timely than those with low perceived similarity (t = 2.37, p < .05). However, when teams had low actual similarity, those with high perceived similarity were much less timely than those with low perceived similarity (t = 4.76, p < .01). The interaction of actual similarity at Time 1 and perceived similarity at Time 2 on timeliness was not significant. The interactions between actual (Time 1 or 2) and perceived at Time 1 were also insignificant. This pattern of results lends support to Hypothesis 6 with both perceived and actual similarity at Time 2, but not at Time 1.

DISCUSSION

This study yielded several significant findings. First, although perceived temporal TMM similarity has not received much attention to date, it exerted a stronger influence on both viability and performance than the actual temporal TMM similarity. Second, we consistently found that teams with a mismatch between actual and perceived similarity experienced lower viability and performance, even lower than those who had both low actual and low perceived similarity. Third, although our hypotheses were agnostic to time, significant differences emerged at Time 1 and Time 2. These findings are discussed below.

First, compared to actual temporal TMM similarity, perceived temporal TMM similarity exerted a stronger influence on both viability and performance. Although expected for viability, perceived TMM similarity unexpectedly influenced team performance more strongly compared to actual TMM similarity. Whereas actual TMM similarity was related to higher performance as predicted, surprisingly, higher perceived TMM similarity was associated with lower performance (less timeliness). Because timeliness was our performance measure, increased or inefficient communication may take up more time, especially in virtual teams, resulting in less timeliness. More communication within a team is typically expected to lead to more liking (DePaulo & Bell, 1990; Lakin et al., 2003) and better coordination of team actions (Cannon-Bowers et al., 1995), which improve performance (e.g., Rico et al., 2008). However, in a virtual team, increased communication may require more time, and misunderstandings may take longer to rectify, which would have a detrimental effect on the performance metric of timeliness. Indeed, virtual teams are prone to receiving and discussing too much irrelevant information, making for dysfunctional information exchange (Ellwart et al., 2015) that may result in lower timeliness. Additionally, multiple members repeating the same information signals that it is important (McLeod, 2013) and is likely to align perceptions of similarity, but may be especially time consuming in virtual teams, decreasing timeliness.

Second, study results demonstrated the importance of the match between actual and perceived temporal TMM similarity in virtual teams. Even more than having both low actual and low perceived TMM similarity, results revealed that mismatches between actual and perceived temporal TMM similarity were particularly detrimental to both viability and performance in virtual contexts. Regarding viability, teams that thought they were in sync and actually were in sync were more likely to desire working together in the future. Viability suffered the most when teams perceived low temporal similarity, but actually had high similarity. However, this relationship was only true when actual and perceived temporal TMM similarity were measured at Time 1 and Time 2, respectively.

Potentially, rapport and understanding impacted by the level of actual temporal similarity in the first round (Gevers et al., 2006) may set the stage for affecting viability, measured after the second round. Perceptions of relationships can develop early and tend to remain consistent thereafter (Liden, Wayne, & Stilwell, 1993). Kimble (2011) notes the importance of members’ first “online impression” in virtual teams, as it influences conversational tones for later discussions. Initial online impressions may be impacted by the actual similarity early on and influence later perceptions of similarity. The early formation of relationship quality as influenced by initial actual similarity may theoretically explain the relationship of the actual temporal TMM similarity at Time 1 interacting with perceptions of similarity at Time 2 to impact viability.

Regarding performance, performance was lower when teams thought they were in sync, but actually were not. Similar to the findings for viability, performance was lowest when teams were actually not on the same page, but perceived they were. This relationship was only true when actual and perceived temporal TMM similarity were measured at Time 2 and not at Time 1, which is consistent with prior findings that temporal TMMs have a greater impact on performance later in a team’s lifespan rather than earlier. Mohammed and colleagues (2015) found that actual temporal TMMs at Time 1 were not significantly related to performance, but temporal TMMs measured at Time 2 were positively related to performance.

Although it was inferred that teams low in both perceived and actual TMM similarity would have lowest performance, mismatches were even more detrimental. Clarkson, Hirt, Jia, and Alexander (2010) reported similar negative outcomes regarding mismatched actual versus perceived depletion. Specifically, individuals that were given feedback stating they should be less depleted (perceived) while in the high depletion condition (actual), or actually had low depletion but were told they should have high depletion, were less persistent in the task, made more errors, and had a longer response time than individuals who were told they should be depleted and were also actually depleted. Overall, teams with mismatches performed worse than those with both low actual and perceived similarity.

Implications

Although not receiving much emphasis in the TMM literature to date (Mohammed et al., 2010), perceived temporal TMM similarity exerted a stronger influence on both viability and performance compared to actual temporal TMM similarity. Team distribution complicates the extent to which members are aware of others’ progress and performance (Schmidtke & Cummings, 2017), making it likely that perceived TMM similarity may differ from actuality. Indeed, including both perceived and actual temporal TMM similarity in the model accounted for additional variance in predicting viability and performance over just one or the other. Considering both, particularly the perceived similarity, appears especially important for virtual teams.

The empirical contribution of measuring both actual and perceived similarity at once allowed for an examination of interactions, which demonstrated that some teams’ perceptions and actual temporal TMM similarity were in agreement whereas others’ were not, as Rentsch and colleagues (2009) proposed. The results of this study corroborated that when teams are not in sync, negative outcomes on viability and performance result. There was a negative effect on viability for teams that had low perceived similarity, but high levels in actuality. For these teams, ratings of team viability were remarkably even lower than teams that had low actual similarity. This resulted in teams that were on the same temporal page, but did not desire to work together in the future due to their misperception.

Additionally, poor performance resulted for virtual teams that had low actual similarity, but perceived high similarity. Teams that rated themselves as having high perceptions of temporal similarity but demonstrated low actual similarity surprisingly were less timely than teams that had low actual similarity and also perceived low similarity.

Results demonstrated that perceived similarity had a stronger effect on viability and performance than actual similarity. Therefore, a practical implication is that perceptions of being in sync do matter and that virtual team members should be aware that perceptions of temporal TMM similarity are important. Study results also revealed the importance of having synchrony between actual and perceived temporal TMM similarity in distributed contexts. When performance or viability is low, it may be beneficial for virtual teams to explore the potential (mis)match between their actual and perceived TMM similarity.

Limitations and Future Directions

Although focusing on under-researched temporal TMMs was a contribution (Mohammed et al., 2012), results may not be generalizable to taskwork or teamwork TMMs. Future research should compare actual versus perceived TMM similarity for taskwork and teamwork content. Similarly, as the performance outcome in this study was timeliness, there are likely a number of additional temporal team inputs and processes such as temporal individual differences within the team and related process conflict (Mohammed, Hamilton, & Lim, 2009) that may also affect team timeliness. Exploring the influence of these variables would also be beneficial. Of note, generalizing the current findings to alternative forms of performance such as quality or quantity of virtual team output should be done cautiously.

A high degree of task interdependence, dynamic events, decision making, and immediate feedback in the NeoCITIES simulation made it an excellent tool to study TMM similarity in a virtual context. However, teams participating in the study only worked together for about two and a half hours, therefore results may be more applicable to newly formed teams. Future research should examine the differences between perceived and actual TMMs in more lengthy projects or long-term teams. In addition, it would be beneficial to examine the impact of TMMs in virtual teams distributed across varying geographical locations and time zones (Schmidtke & Cummings, 2017).

As the content of the concept maps was based specifically on the NeoCITIES simulation (ordering the units to respond to a particular event), it was necessary to collect these measures following the performance rounds so participants were familiar with the content (Ellis, 2006). Therefore, causality cannot be claimed. Future studies should incorporate an experimental design.

Another direction for future research is to include more measurement time points. Due to the time-consuming nature of the training required for the simulation and the added difficulty of measuring concept maps, it was feasible to only have two measurement points and performance rounds (Mohammed et al., 2015). However, it would be beneficial to develop a more thorough understanding of the nature of actual and perceived TMMs over time in virtual contexts by incorporating more time points, potentially in a long-term team setting.

Because not being in sync is detrimental to performance and viability outcomes in virtual teams, researchers should explore methods of getting in sync. One possibility is cross-training as a training technique to better align perceptions of temporal TMM similarity with actual levels. Cross-training can improve interpersonal knowledge by learning about duties of other team members, which contributes to team shared understanding (Blickensderfer et al., 1998). Therefore, cross training may prove particularly useful for developing similar TMMs in virtual teams (Schmidtke & Cummings, 2017), as this process is particularly complex in distributed contexts (Ellwart et al., 2015).

Conclusion

Despite the prevalence of TMM studies, “there is a dearth of empirical research investigating the role of shared cognition in the virtual team literature” (Schmidtke & Cummings, 2017, p. 673). Answering this call, we examined the impact of perceived and actual temporal TMM similarity on performance and viability in virtual teams. Compared to actual temporal TMM similarity, perceived temporal TMM similarity exerted a stronger influence on both viability and performance. Additionally, mismatches between actual and perceived TMM similarity were particularly detrimental to outcomes. When teams think they are temporally in sync but were actually not, performance declined. When teams perceived low levels of sharedness but held high actual similarity, viability decreased. Despite receiving little attention in the TMM literature, results highlight the importance of perceived temporal TMM similarity in addition to actual TMM similarity.

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O Expertise and Distributed Team Cognition

A Critical Review and

 
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