The Role of Transactive Memory in the Performance of Multiteam ...

Responding Effectively to Civil Emergencies: The Role of Transactive Memory in the Performance of Multiteam Systems Mark P. Healey Leeds University Business School University of Leeds [email protected]

Gerard P. Hodgkinson Leeds University Business School University of Leeds [email protected]

Swee Teo Republic of Singapore Navy [email protected] ABSTRACT

Motivation Many of today’s most significant organizational challenges require the effective collaboration of collectives of various teams. Nowhere is the performance of such multiteam systems more important than in responding to civil emergencies. Research approach This field study analyses the determinants of performance among multiteam systems responding to civil emergencies in training exercises. Findings Transactive memory – meta-knowledge of other’s expertise – is critical for team and system performance, operating at both the level of individual component teams and the wider multiteam systems. Different forms of training exercise can yield differential outcomes in terms of transactive memory. Research implications We discuss the implications for research on multiteam systems and for the design of training interventions designed to develop transactive memory among emergency responders. Originality/value This is the first study to examine empirically the role of transactive memory in the performance of multiteam systems. Keywords: Multiteam systems, transactive memory, shared cognition, team performance

INTRODUCTION

The responsibility for tackling many of today’s most significant organizational challenges often lies with different teams working together. Complex tasks such as the development of new drugs, major engineering projects and military operations rely not on a multitude of individuals, nor single teams or even entire organizations, but the collaboration of multiple teams with a common purpose. Mathieu, Marks and Zaccaro (2001) articulated the concept of ‘multiteam systems’ to describe this form of activity. A multiteam system (MTS) constitutes two or more teams interfacing directly and interdependently to attain collective goals. Nowhere is the efficient coordination of multiple teams more critical than in responding to civil emergencies. When disaster strikes, various agencies come together in a system comprising inter-agency and single-agency teams to produce a localized response, from police, fire, and ambulance services to the private sector firms often plunged into crisis. Analyzing the workings of emergency responses from a MTS perspective promises to shed new light on the factors that determine effective responding under the unique circumstances that characterize civil emergencies. However, existing attempts to validate the MTS concept have been limited to laboratory simulations with student participants (DeChurch and Marks 2006; Marks et al. 2005). The purpose of this study is to analyze from a MTS perspective the determinants of effective performance among collectives tasked with responding to civil emergencies. In so doing, we seek to provide an initial validation of the MTS concept for the naturalistic study of effective functioning among complex constellations of teams during civil emergencies. Analyzing intra- and inter-team coordination among professional emergency responders operating in demanding naturalistic contexts will potentially yield a far richer understanding of the operation of MTSs than studies conducted within the sparse confines of the laboratory.

© The Authors 2009. Published by the British Computer Society Proceedings of NDM9, the 9th International Conference on Naturalistic Decision Making 53 London, UK, June 2009

Healey • Hodgkinson • Teo Responding Effectively to Civil Emergencies

MULTITEAM SYSTEMS

The concept of MTS differs from prior models of organization because the latter fail to explain the dynamics of how teams interact to create an effective system. Mathieu and colleagues outline five defining features of MTSs (see also Marks et al. 2005; DeChurch and Marks 2006). According to this original conception, MTS: (i) are composed of two or more teams, (ii) are discrete entities larger than individual teams but smaller than the organizations within they are embedded, (iii) comprise component teams that exhibit input, process and outcome interdependencies with at least one other team, (iv) are open systems whose configuration stems from environmental demands, and (v) have component teams, which may not share proximal goals but do share one or more common distal/superordinate goals. Building on the above work, we suggest that coordination within and between teams is the most important determinant of the effective functioning of MTSs responding to civil emergencies. This notion resonates with UK government guidelines emphasizing that, “rapid implementation of arrangements for collaboration, co-ordination and communication are ... vital.” (HM Government 2005). We define coordination as activities that enable individuals and groups to effectively sequence and time interdependent actions directed toward task goals (cf. DeChurch and Marks 2006). Coordination involves monitoring, evaluating, anticipating and reacting to the actions of others to ensure that the actions of the collective are effective in terms of addressing its goals. Coordinated activity within and between the diverse teams involved in civil emergencies is critical for rapid decision making, the selection and implementation of appropriate courses of action, and effective deployment of human and technical resources. Yet, multi-stakeholder coordination is notoriously difficult, particularly under the complex, uncertain, high-stakes and time-pressured circumstances that characterize civil emergencies. Although all four of the above factors potentially contribute to effective coordination, the most fundamental and immediate determinant concerns the extent to which members possess requisite understandings of the system and the tasks they face. A voluminous literature analyzing team performance shows that effective coordination is contingent upon the emergence of an appropriate collective understanding of the behaviours required to meet the team’s goals (for reviews, see Hodgkinson and Healey 2008; Salas and Cannon-Bowers 2001; Salas and Fiore 2004; Cannon-Bowers et al. 1993; Klimoski and Mohammed 1994; Kozlowski and Ilgen 2006). Smith and Dowell’s (2000) case study of the management of a major railway accident provides a telling example. This study highlighted how emergency responders from various agencies failed to develop a shared mental model of the decision making process and the people involved, such that a lack of common understanding became a major barrier to inter-agency coordination. We contend that one particular form of collective understanding, transactive memory, is especially critical to the performance of MTSs during civil emergencies. TRANSACTIVE MEMORY IN MULTITEAM SYSTEMS

Within a multi-team system, knowledge resides in component teams. Each team potentially possesses unique knowledge, skills and resources crucial to the performance of some part of the overall task. During an emergency, it is critical for responders to know where to find the necessary knowledge and expertise located within the wider system, and how to access and apply these resources with rapidity. Furthermore, teams must be aware of the roles and capabilities of other teams, to facilitate access to the full resources at the system’s disposal and ensure smooth coordination. Researchers refer to this form of group cognition as a transactive memory system (TMS): a shared system for encoding, storing, and retrieving information (Wegner 1987, 1995; Wegner, Erber and Raymond 1991; see also Hollingshead 1998a, 1998b).

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MTS Level

MTS Transactive Memory

MTS Communication

MTS Performance

Team Level

Team Transactive Memory

Team Communication

Team Performance

Input

Process

Outcome

Figure 1. Effects of Transactive Memory on Team and System Performance

Responding to an emergency through multi-team systems requires coordination both within and between teams. First, individual component teams (e.g. central command team, incident control team, technical advice team) must utilize the knowledge and expertise of their own internal members to ensure their team cooperates effectively and acts decisively. Second, teams need to be aware of the expertise, resources and responsibilities of other teams within the wider system so that the system coordinates its activities and deploys its resources optimally. To coordinate an emergency response, transactive memory must function at both the level of component teams and the level of the overarching system (See Figure 1). We theorize that transactive memory aids performance during emergencies by improving the quality of communications within and between teams. An awareness of the information and expertise held by others enables responders to retrieve and process that information more effectively, and act decisively based on this information. Understanding of others’ responsibilities enables responders to communicate clear instructions and avoid misallocation of tasks and duplication of effort. Moreover, a well developed transactive memory helps responders avoid transmitting information that is unnecessary, ambiguous, or inaccurate in the hands of recipients. Transactive memory enables responders to transmit the right information to the right people at the right time, increasing the likelihood that responders act on valid assumptions. In this way, transactive memory helps develop team situation awareness (Salas et al. 1995). In sum, we maintain that team transactive memory influences team performance via its influence on team communications. We expect similar effects at the MTS level: system transactive memory should enhance communications and thus relate positively to the performance of the system as a whole. We theorize that the performance of individual teams influences the performance of the wider system. However, MTS transactive memory and MTS communication should predict MTS performance beyond the combined effects of transactive memory, communication and performance at the level of the individual teams, since the performance of the system is more than the sum of its component teams. RESEARCH METHOD, MEASURES AND PROCEDURE

We studied the performance of three MTSs as they undertook emergency response training exercises held in the North of England during summer 2008: exercises Alpha, Beta, and Gamma. The three exercises employed different designs: exercise Alpha was a facilitated tabletop, exercise Beta was a collocated simulation, while exercise Gamma was a distributed simulation. The purpose of each exercise was to test the robustness of the elements of the emergency response system, including emergency plans, systems, procedures and routines. Across the three exercises, 72% of the 143 total participants were male. The exercises involved between 11-19 different organizations, and each exercise involved representatives from the police, fire, and ambulance services, regional and local government, private sector firms, environmental agencies, utility companies, health service organizations, and the media.

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The research team attended all three exercises as observers, and presented all exercise participants with a questionnaire pack at the end of the exercise, which they completed before leaving. We measured TMS, communication and performance, each at two levels of analysis: (i) individual component teams, and (ii) the wider MTSs. Measures Team transactive memory (T-TM). We measured team transactive memory using Lewis’s (2003) transactive memory system scale, selected due to its sound psychometric properties and applicability in field settings. This scale comprises 15 items tapping three underlying dimensions of transactive memory, namely specialization, credibility and coordination. Sample items include, “I know which team members have expertise in specific areas” (specialization), “I was confident relying on the information that other team members brought to the discussion” (credibility), and “our team worked together in a well-coordinated fashion” (coordination). Responses to all items were based on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree). The overall measure demonstrated adequate internal consistency (α = 0.79). MTS transactive memory system (MTS-TM). We measured MTS-TM by adapting the transactive memory system scale (Lewis, 2003), changing the unit of analysis of each of the 15 items to ask individuals to reflect on their knowledge of the wider MTS and awareness of and trust in other teams’ capabilities. Sample items included, “I know which teams have expertise in specific areas” and “the various teams worked together in a well-coordinated fashion”. Responses to all items were based on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree). The MTS-TM scale demonstrated high overall internal consistency (α = 0.82). Team Communication (TC). We measured intra-team communication using a communication quality scale developed by Mohr and Spekman (1994). This 7-item scale included the items, “communication within our team was timely” and “the information shared within our team was accurate”. Participants recorded responses on a 5-point scale ranging from 1 (not at all) to 5 (to a great extent). The scale exhibited high internal consistency (α = 0.92). MTS Communication (MTS-C). We measured communication at the level of the multiteam system (i.e. inter-team communication) via an adapted version of the communication quality scale, changing the unit of analysis from individual teams to the whole MTS. Example items included, “communication between the teams was timely” and “information shared between teams was accurate”. Like its team level counterpart, this scale demonstrated high internal consistency (α = 0.93). Team Performance (TP). The components of team performance are highly context-dependent, with the effective performance of different types of task requiring specific skills, behaviours and activities; hence assessing team performance demands a bespoke measure (Cohen and Bailey 1997; Ancona and Caldwell 1992). In the current context, we identified nine critical elements that underpin the generation of an effective emergency response: quality of decision making, efficiency, quality of team’s contribution to the emergency response, ability to complete the task on time, speed of response to events, innovativeness, ability to make the most of its resources, quality of leadership, and overall performance. The nine elements identified apply equally at the team and system levels of analysis. Participants rated each element on a 5-point scale anchored at endpoints ranging from 1 (very poor) to 5 (very good). Applied to the individual team level of analysis, this 9-item scale demonstrated high internal consistency (α = 0.94). Table 1 Means, Standard Deviations, and Correlations

1. Age 2. Sex 3. Emergency tenure 4. Team transactive memory 5. Team communication 6. Team performance 7. MTS transactive memory 8. MTS communication 9. MTS performance * **

Mean 40.94

S.D. 8.10

1.

2.

3.

4.

5.

6.

7.

8.

.70 15.91 3.88

.46 8.64 .41

3.71 3.77 3.67

.67 .69 .43

3.08 3.41

.80 .68

.38** .51** -.04 -.21 -.15 -.34* -.53** -.36*

.29* -.01 -.08 .17 -.27* -.27* -.26

.14 .04 .06 -.25 -.07 .03

.52** .56** .48** .28** .36**

.73** .48** .42** .39**

.59** .40** .57**

.66** .74**

.67**

Correlation is significant at p< 0.05 (2-tailed) Correlation is significant at p < 0.01 level (2-tailed).

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Multi-team System Performance (MTS-P). We measured the performance of the entire multiteam system using the 9item scale outlined above, adapting the items to change the unit of analysis from component teams to the wider system. We instructed participants to use the nine items to, “rate the performance of the group overall (i.e. all teams participating in the exercise) in terms of its ability to complete the task”. The scale demonstrated high internal consistency (α = 0.93). RESULTS

Of the total number of participants in the three exercises (n=143), we obtained full responses from 119 individuals (83%). Table 1 shows descriptive statistics and inter-correlations for the study variables. We employed hierarchical regressions and mediation analysis to test our predictions that transactive memory would be a significant positive predictor of performance via its influence on communication, at both the component team and MTS levels of analysis. Team performance We first conducted hierarchical regression by entering the two dummy variables, team transactive memory, and team communication as blocks of predictors of team performance. The results in Table 2 show that team transactive memory and team communication are significant positive predictors of team performance, but that entering communication into the equation diminishes the effects of transactive memory. We tested the theorized mediating effect of communication more formally using the procedure suggested by Baron and Kenny (1986). The data met the requirements for mediation analysis: transactive memory was a significant positive predictor of team communication (β = .45, ∆ R2 = .20, ∆ F = 29.77, p < .001) and team performance (β = .50, ∆ R2 = .24, ∆ F = 35.33, p < .001), and team communication was a significant positive predictor of team performance (β = .72, ∆ R2 = .48, ∆ F = 107.75, p < .001). To test communication as a mediator, we entered team transactive memory into the regression equation for team performance after controlling for communication: team transactive memory accounted for a significant increment in variance in performance (∆ R2 = .03, ∆ F = 8.29, p < .01). Hence, it appears that team communication mediates partially the effects of team transactive memory on team performance.

Independent variables Exercise alpha (dummy) Exercise beta (dummy) Team transactive memory Team communication R2 ∆ R2 ∆F

Table 2 Regression Results for Team Performance Model 1 Model 2 β β .044 .029 -.174 -.086 .496*** .020 .038 2.127

.255 .237 35.334***

Model 3 β -.087 -.048 .214** .621*** .536 .278 66.543***

*

Significant at p < .05 Significant at p < .01 *** Significant at p < .001 **

Independent variables Exercise Alpha (dummy) Exercise Beta (dummy) Team communication Team transactive memory Team performance MTS transactive memory MTS communication R2 ∆ R2 ∆F

Table 3 Regression Results for MTS Performance Model 1 Model 2 Model 3 β β β -.017 -.027 .011 -.447*** -.359*** -.196** .053 -.040 -.072 -.104 .512*** .294** .547*** .180 .194 13.15***

.401 .234 14.45***

*

Significant at p < 0.05 Significant at p < 0.01 *** Significant at p < 0.01 **

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.571 .167 42.85***

Model 4 β -.056 -.154* -.018 -.145 .306** .355*** .332*** .624 .053 15.74***


Multi-team system performance Initial hierarchical regression analysis revealed that, similar to the results at the team level, MTS transactive memory and MTS communication relate positively and significantly to MTS performance, but that entering MTS communication into the equation diminishes the effects of transactive memory. We again tested the theorized mediated model using Baron and Kenny’s (1986) procedure. We first corroborated that MTS transactive memory was a significant predictor of both MTS communication (β = .58, ∆ R2 = .29, ∆ F = 63.02, p < .001) and MTS performance (β = .67, ∆ R2 = .36, ∆ F = 88.58, p < .001), while MTS communication was a significant predictor of MTS performance in its own right (β = .68, ∆ R2 = .30, ∆ F = 63.63, p < .001). Entering MTS transactive memory into the regression equation for MTS performance after controlling for the effects of MTS communication showed that MTS transactive memory accounted for an additional 12% of the variance in MTS performance: ∆ R2 = .12, ∆ F (1, 107) = 31.78, p < .001. MTS communication only mediates partially the effects of MTS transactive memory on MTS performance. Hence, as theorized, transactive memory appears to influence performance indirectly via its effects on communication. To examine the ability of system level variables to predict system performance over and above the team level variables, we undertook a final hierarchical regression analysis. Table 3 shows the results. The findings illustrate that only the performance of individual component teams is a significant positive predictor of multiteam system performance. However, after controlling for the effects of team level variables (transactive memory, communication and performance), both MTS transactive memory (∆ R2 = .17 ∆ F (1, 107) = 42.85, p < .001) and MTS communication (∆ R2 = .05, ∆ F (1, 107) = 15.74, p < .001) explain significant additional variance in MTS performance. The results of MANOVA analysis showed a significant main effect of exercise design on MTS TMS, communication, and performance (F (6, 103) = 6.89, p < .001, η 2 = .16). Post-hoc Scheffé tests on mean differences showed that the collocated simulation (exercise Beta) demonstrated significantly lower levels of TMS than both the facilitated tabletop (exercise Alpha) and the distributed simulation (exercise Gamma) (p’s < .05). DISCUSSION AND CONCLUSIONS

The MTS concept developed by Mathieu et al. (2001) potentially holds considerable value as a means of conceptualizing the factors that determine the performance of multi-agency collectives brought together to tackle civil emergencies. However, current attempts to validate the MTS concept have been limited to laboratory-based studies (Marks et al. 2005; DeChurch and Marks 2006). The present study provides an initial examination of the operation of MTSs in more naturalistic settings. Prior research highlights the role of collective cognition as a key determinant of MTS coordination and performance. The current study focussed on the role of transactive memory — meta-knowledge about others’ knowledge, skills and behaviour patterns. Specifically, we examined the role of transactive memory systems in the performance of three actual multiteam systems participating in training exercises involving simulated civil emergencies. While previous research emphasizes the role of shared mental models in MTS performance (Mathieu et al. 2001; Marks et al. 2005; DeChurch and Marks 2006), our results suggest that effective MTS performance is contingent upon the development of transactive memory within both component teams (i.e. intra-team transactive memory) and the wider system in which they operate (i.e. inter-team transactive memory). The results support the idea that effective MTS performance is contingent upon the development of transactive memory at two levels: the level of component teams (i.e. intra-team transactive memory) and the MTS level (i.e. inter-team transactive memory). At both levels of analysis, transactive memory exerted a significant influence on performance via the quality of communication. Moreover, although the performance of component teams was a significant predictor of overall MTS performance, transactive memory at the MTS level was predictive of MTS performance over and above the performance of individual teams. Previous research has emphasized the importance of shared mental models to MTS performance (Mathieu et al. 2001; Marks et al. 2005; DeChurch and Marks 2006). In contrast, our findings illustrate that performance may be contingent not so much on MTS members holding a common understanding of teams and tasks, but rather depends on members’ awareness of other’s expertise and response patterns, and their ability to trust and utilize other’s capabilities. Perhaps the most intriguing finding of the present study is that the development of transactive memory at the system level differed according to training exercise design. Although further research is needed to establish the reliability of these findings, given the importance of transactive memory to communication and performance, designers of emergency responder training exercises should adopt as a key goal the development of transactive memory within the multi-team systems responsible for responding to civil emergencies. Moreover, trainers should consider how different exercise designs can yield varying cognitive outcomes, and configure designs appropriately for the development of transactive memory.

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ACKNOWLEDGEMENTS

The authors are grateful to the Emergency Planning College of the UK Cabinet Office for facilitating research access for the study reported here; in particular, we acknowledge the support and advice of Dr Robert MacFarlane. REFERENCES

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