This chapter begins with a discussion of the definition of leadership and the degree to which it is distinct from management. We then review the expansive parallel literatures on team and organizational leadership in contexts outside of science. Through the lens of established leadership theories, models, and behaviors, we identify those approaches that are relevant to science teams and larger groups and for which there is research evidence for enhanced team or group effectiveness. Next, we summarize the research evidence on team science leadership. We then discuss professional leadership development for team science leaders. We then use the research evidence as a guide to consider how leadership strategies can address the challenges for team science created by the seven features outlined in Chapter 1 and conclude with a conclusion and a recommendation for the future leadership of science teams and groups.
Our study charge calls for consideration of how different management approaches and leadership styles influence the effectiveness of team science. The distinction between management and leadership has been defined in the research literature in multiple ways. For example, Kotter (2001, p. 85) proposed that leadership and management are “two distinctive and complementary systems of action.” Kotter (2001) proposed that the main functions of leadership are to set direction, to align people, and to motivate and inspire them, while the main functions of management are to develop concrete plans for carrying out work, to allocate resources appropriately, to
create an organizational structure and staffing plan, and to monitor results and to develop problem-solving strategies when needed. However, Drath et al. (2008, p. 647) pointed out that these functions are not necessarily mutually exclusive: “alignment is often achieved through structure and many of the aspects of shared work usually categorized as management, such as planning, budgeting, supervisory controls, performance management, and reward systems.” Recognizing that it is difficult, if not impossible, to draw a strict line between leadership and management, we have not attempted to completely disentangle the two functions. Therefore, while this chapter focuses primarily on leadership, the research discussed also addresses aspects of management (as defined by some scholars). Management of organizations that house science teams is discussed further in Chapter 8.
Over half a century of research on leadership has highlighted the nuances and complexities of leading individuals, teams, and organizations. Some leaders are born with the skills and abilities to guide followers, while other leaders are trained through education and opportunities for hands-on experience. Those who lead large organizations successfully are not necessarily successful at leading small groups. Some leaders are charismatic and have a commanding presence in a crowd while other leaders build trust and respect through one-on-one relationships. In short, leadership is not a quality that an individual either has or lacks, and there is not a single leadership style that is effective in all contexts. Rather, leadership is multifaceted, encompassing different ways in which individuals exhibit leadership as well as different environments in which leadership occurs. Leaders’ approaches to their team or group members may vary depending upon the nature of the task and goals for the team, as well as the composition of the team. In some cases, a directive, task-oriented approach may be called for, while in other cases, leaders strive to support and encourage team members’ ideas, innovations, problem identification, and proposed solutions.
This chapter will show that researchers have focused on many aspects of leadership, including specific leader behaviors, their interactions with followers, and contingent factors that guide how effective a leader is in a given situation.
This general leadership theory and research can inform the emerging field of team leadership, yet it must be noted that leadership quality is very difficult to measure or evaluate; in the research to date, the most common criterion for leadership effectiveness is the subordinates’ perception of the effectiveness of their leader, rather than direct measures of team performance. Nonetheless, meta-analytic findings from this extensive literature
provide indications of the potential value of leadership in promoting team effectiveness (Kozlowski and Ilgen, 2006). In this section, we review the research evidence for the impact of behavioral, relational, transformational, transactional, contingency, and contextual approaches to leadership, with particular emphasis on contextual approaches. Each of these approaches entails different behaviors on the part of leaders (and in one case—the relational approach—also emphasizes the behavior of followers), but they are not necessarily mutually exclusive and a single leader can employ multiple approaches.
Influential studies conducted at the Ohio State University in the 1950s identified two overarching features of a behavioral approach to leadership: consideration (i.e., supportive, person-oriented leadership) and initiating structure (i.e., directive, task-oriented leadership) (Day and Zaccaro, 2007). Team outcomes have been found to be significantly correlated with both features, suggesting that this classic approach is potentially viable for team leadership as well (Judge, Piccolo, and Ilies, 2004). An advantage of this behavioral approach is its focus on observable leader behaviors rather than personality traits, allowing many of its core elements of this approach to be used with other leadership approaches, especially the transformational approach, discussed below (Bass and Riggio, 2006).
The relational approach, or leader-member exchange theory (LMX), describes the dyadic relationship between leaders and followers, or subordinates. Research shows that followers who negotiate high-quality exchanges with their leaders experience more positive work environments and more effective work outcomes (Gerstner and Day, 1997; Erdogan and Bauer, 2010; Wu, Tsui, and Kinicki, 2010). In this view, team leaders become especially important for shaping team members’ perceptions of their shared environment and of team relationships (Kozlowski and Doherty, 1989; Hofmann, Morgeson, and Gerras, 2003).
The transformational approach, the most dominant leadership paradigm over the past decade, focuses on leadership styles or behaviors that induce followers to transcend their interests for a greater good (Kozlowski and Ilgen, 2006; Day and Antonakis, 2012). Transformational leadership
encompasses the behavioral dimensions of charisma, inspirational motivation, intellectual stimulation, and individualized consideration.
While the transformational approach may be of particular relevance to teams, it has been studied mainly at the individual level of analysis, assessing how leaders using this approach influence individual followers1 and outcomes rather than team-level outcomes. In one of the few studies looking specifically at teams, Lim and Ployhart (2004) found the transformational approach to be more strongly related to performance in maximal-performance than in typical-performance contexts, supporting the notion that transformational leadership facilitates subordinate motivation and effort.2 Other studies have linked the transformational approach to facets of a team’s collective personality and to its performance/profitability (Hofmann and Jones, 2005). Of direct relevance to science teams, recent research has demonstrated the multilevel and cross-level influences of transformational leadership on the effectiveness of innovation teams (Chen et al., 2013). In another example of the multilevel influences of organizational and team leadership, Schaubroeck et al. (2012) found that higher-level leaders influence lower-level leaders and teams by serving as leader models to emulate and by crafting cultures that influence the lower level via alternative pathways.
The transactional approach (Bass, 1985) entails leader behaviors aimed at negotiating mutually beneficial exchanges with subordinates. These behaviors can encompass contingent rewards, including clear expectations and linkages with outcomes, active management by exception (i.e., proactive and corrective action), and passive management by exception (i.e., reactive management after the fact).
Contingency and Contextual Approaches
The contingency approach matches the leader’s behavior to the context to maximize outcomes and leadership effectiveness. This emphasis on context should be relevant to teams engaged in complex tasks, as is the case for science teams (Dust and Zeigert, 2012; Hoch and Duleborhn, 2013). While
1 For leaders to exercise influence, followers must allow themselves to be influenced (Uhl-Bien and Pillai, 2007). For a discussion of followership theory and a review of research related to followership, see Uhl-Bien et al. (2014).
2Maximal-performance contexts involve tasks of relatively short duration in which team members are aware that performance is being evaluated and accept that that maximal performance is expected on the task (Sackett, Zedeck, and Fogli, 1988, as cited in Lim and Ployhart, 2004).
the contingency approach is no longer active in current research, it has been tied to the development of a contextual approach to leadership. As its name suggests, this approach emphasizes a more contextual perspective that recognizes the need to use a combination of approaches to meet the leadership requirements of particular situations (Hannah et al., 2009; Simonton, 2013; Hannah and Parry, in press). For example, the contextual circumstances of a particular team might require shared leadership, in which leaders share leadership roles, functions, and behaviors among team members. Shared leadership can be formally appointed at the outset of an endeavor or can emerge during the course of an activity (Mann, 1959; Judge et al., 2002). Leadership emergence involves both the extent to which an individual is viewed as a leader by others in the group (Lord, DeVader, and Alliger, 1986; Hogan, Curphy, and Hogan, 1994; Judge et al., 2002), as well as the degree to which an individual exerts influence on others (Hollander, 1964).
Contextual leadership should not be viewed as either hierarchal or shared. Instead, research suggests that teams engaged in a combination of both hierarchal and shared forms of leadership have the best outcomes (Pearce and Sims, 2002; Pearce, 2004; Ensley, Hmielski, and Pearce, 2006). Understanding ways in which more traditional and hierarchical leadership may be used in conjunction with more participative, shared, or otherwise emergent forms of leadership is particularly relevant for effective leadership of science teams and groups. For example, based on extensive, repeated interviews, Hackett (2005) found that the directors of successful microbiology laboratories at elite research universities used and valued both directive, hierarchical leadership and shared, participative leadership styles. It is also important to understand how shifts in leadership hierarchies occur in science teams and groups and how best to manage these shifts, depending on the stage of the research project or the expertise needed at different times.
The general leadership theories delineated in the previous section have useful, but only indirect, implications for team effectiveness (Kozlowski and Ilgen, 2006). In part, this is because they focus on a general set of behaviors that are broadly applicable across a wide variety of situations, tasks, and teams. They neglect unique aspects of specific team tasks and processes and the dynamic processes by which team members develop, meld, and synchronize their knowledge, skills, and effort to be effective as a team (Kozlowski et al., 2009).
Leadership and Key Team Processes
As discussed in Chapter 3, team processes have been shown to be connected to team effectiveness, and existing research demonstrates that leadership can influence several of these team processes: team mental models, team climate, psychological safety, team cohesion, team efficacy, and team conflict. Leader behaviors that can influence each of these behaviors in ways that enhance team effectiveness are described below and summarized in Table 6-1.
Several leader behaviors can influence the development of team mental models. Marks, Zaccaro, and Mathieu (2000) found that when leaders provided pre-briefs describing appropriate strategies for carrying out team tasks, there were positive effects on team mental models, as well as team processes and performance. Other research has linked leader pre-briefs/
TABLE 6-1 Team Processes That Are Influenced by Leader Behaviors
|Process||Leadership Behaviors That Influence the Process|
|Team Mental Models||
discussions of planning strategies and debriefs/feedback to the development of team mental models (Smith-Jentsch et al., 1998; Stout et al., 1999).
Leadership can have a significant influence on team climate. Leader practices that define the mission, goals, and instrumentalities for teams can shape team climate (James and Jones, 1974), as do communications from team leaders, particularly in terms of what leaders emphasize to team members (Kozlowski and Doherty, 1989; Zohar, 2000, 2002; Zohar and Luria, 2004; Schaubroeck et al., 2012).
Psychological safety is a facet of team climate. Team leaders can foster a climate of psychological safety through coaching, reducing power differentials, and encouraging inclusion (Edmondson, Bohmer, and Pisano, 2001; Edmondson, 2003; Nembhard and Edmondson, 2006).
While research on the antecedents of team cohesion is limited, theory suggests that developmental efforts by team leaders (e.g., Kozlowski et al., 1996, 2009) are likely to have a strong influence on the team’s formation and maintenance. Newcomers to teams tend to “respond positively to leader efforts to convey social knowledge, promote inclusion, and communicate acceptance” (Kozlowski et al., 1996, p. 269, citing Major and Kozlowski, 1991). Kozlowski and colleagues (1996) proposed that several leader behaviors therefore promote the development of team cohesion, including explicitly defining social structure, promoting open communications, and modeling self-disclosure.
Kozlowski and Ilgen (2006) identified several leadership behaviors that can influence the development of team efficacy. One such behavior is creating mastery experiences that enable team members to build individual self-efficacy, and then shifting the focus of team members toward the team’s efficacy. Leadership efforts related to task direction and socio-emotional support have also been found to predict team efficacy (Chen and Bliese, 2002, as cited in Kozlowski and Ilgen, 2006).
As discussed in Chapter 3, team conflict, particularly within diverse teams such as interdisciplinary or transdisciplinary science teams, may be inevitable. Leaders can minimize the harmful effects of conflict on team effectiveness by actively employing conflict management strategies. Marks, Mathieu, and Zaccaro (2001) identified two approaches to conflict management: preemptive and reactive. Preemptive approaches involve anticipating conflict in advance and guiding team members through the process of resolving conflict by establishing cooperative norms, charters, or other structures. In a study of 32 graduate student teams, Mathieu and Rapp (2009) found that the quality of team charters was related to the quality of the teams’ performance. Reactive approaches involve guiding team members in working through conflicts, employing the following strategies: specifying the nature of the disagreement and encouraging team members to develop solutions to the problem, and fostering willingness to accept
differences of opinion, openness, flexibility, and compromise (Kozlowski and Ilgen, 2006).
Based on their analysis of in-depth interviews with members of successful and unsuccessful science teams and larger groups, and building on an earlier guide to team science (Bennett, Gadlin, and Levine-Finley, 2010), Bennett and Gadlin (2012) proposed the use of pre-emptive approaches to manage conflict. Specifically, they suggested that team leaders and members develop explicit collaborative agreements at the beginning of a new research project, articulating how decisions will be made, how data will be shared, how authorship of publications will be handled, and other matters. The process of developing such plans requires the members to discuss and reach agreement on potentially divisive issues in advance, building trust within the team.
Leadership as a Dynamic Process
Team leadership involves the ability to direct and coordinate the activities of team members; assess team performance; assign tasks; develop team knowledge, skills, and abilities; motivate team members; plan and organize; and establish a positive climate (Salas, Sims, and Burke, 2005). This is consistent with research that proposes a functional approach to understanding team leadership structures and processes (Morgeson, DeRue, and Peterson, 2010), conceptualizing effectiveness in terms of team needs, satisfaction, and goal accomplishment (Kozlowski and Ilgen, 2006).
This functional approach treats team leadership as a dynamic process necessitating adaptive changes in leader behavior, as opposed to treating it as a fixed set of static and universal behavioral dimensions. This implies that leaders must strive to be aware of the key contingencies that necessitate shifts in leadership functions, and they must work to develop the underlying skills needed to help the team maintain fit with its task environment and resolve challenges. Dynamic leadership is a process, not a destination; in other words, dynamic leaders recognize that they must always continue to adapt their behavior to best meet the changing needs of evolving projects. Given the dynamic nature of scientific research, leaders of science teams and groups may be more successful if they adopt a dynamic or functional leadership approach, are psychologically agile, and can use appropriate and varied modes of communication to engage with people from multiple generations, backgrounds, and disciplines.
Researchers at the Center for Creative Leadership proposed an approach that might hold promise for effectively incorporating both hierarchical and shared forms of leadership as is necessary in interdependent science teams (Drath et al., 2008). They proposed that setting direction, creating alignment, and building commitment is essential among people engaged in
shared work, and argued that any action that enables these three elements to occur is a source of leadership. This source could be an individual, a collection of individuals, the task itself, or the external environment. An advantage of this approach is that rather than offering a lengthy list of various leadership functions and behaviors (or competencies), the focus is on just the three core leadership tasks: setting direction, creating alignment, and building commitment.
These core leadership tasks are relevant to teams and can be used as a way to understand the dynamic nature of team processes. For example, Kozlowski and Ilgen (2006) proposed that team effectiveness occurs when team processes are aligned with environmentally driven tasks. The core leadership task of creating alignment is consistent with this dynamic conceptualization of team effectiveness. In this sense, team leadership involves all processes that serve to improve team effectiveness. This type of leadership generally evolves throughout the life cycle of a team as the necessary tasks at hand are constantly changing.
Dynamic models of team leadership have two primary foci centered on task cycles or episodes, and the process of team skill acquisition and development. By harnessing cyclic variations in team task cycles to the regulatory processes of goal setting, monitoring/intervention, diagnosis, and feedback, the leader is able to guide team members in the development of targeted knowledge and skills—the cognitive, motivational/affective, and behavioral capabilities that contribute to team effectiveness. There is research evidence in support of this approach to team leadership from a meta-analysis of 131 effects relating team leadership to team performance, which found that team performance outcomes were associated with both task- and person-focused leadership (Burke et al., 2006). Specifically, Burke et al. (2006) found that task-focused leadership had a moderate positive effect on perceived team effectiveness (r = .33) and team productivity/quantity (r = .20), while person-focused leadership had almost no effect on perceived team effectiveness (r = .036), a moderate positive effect on team productivity/quantity (r = .28), and a larger positive effect on team learning (r = .56). Importantly, task interdependence was also shown to be a significant moderator in that leadership had a larger effect when task interdependence was high. The results of this research suggest that leadership in teams influences team performance outcomes by shaping the way team members work with core tasks, and by attending to the socio-emotional needs of the team.
A theory of dynamic team leadership, developed by Kozlowski and colleagues (Kozlowski et al., 2009), elaborates on the role of the formal leader in the team development process in helping the team move from relatively novice to expert status and beyond while building adaptive capabilities in the team. In these latter stages of team development, the team takes on more responsibility for its learning, leadership, and performance. In this
manner, vertical and shared leadership operate sequentially with a formal leader helping the team prepare itself to take on the core functions of leadership and learning. Thus, building adaptive team capabilities or collective leadership capacity (Day, Gronn, and Salas, 2004) is an important team leadership challenge.
Tannenbaum and colleagues (2012) observed that the evolving drive for collaborative leadership reflects the changing nature of teams and the environments in which they operate. As team or larger group size increases, it becomes necessary for leaders to distribute certain leadership tasks, empower team members for more self-management, and create good learning opportunities for the members.
Current research suggests that team empowerment is facilitated by supportive organizational structures (Hempel, Zhang, and Han, 2012); team-based human resource policies for training, development, and rewards (Adler and Chen, 2011); and team-based and external reinforcing leaders (Kirkman and Rosen, 1999). Chen and Tesluk (2012) identified individual-level, team-level, and organizational-level antecedents to team empowerment. At the individual level, self-view, degree of self-efficacy, and need for achievement; job characteristics (such as level of ambiguity and unit size); and the quality of relationships with supervisors and coworkers influence team empowerment. At the team level, leadership behaviors, team climate, and team work characteristics can influence team empowerment. At the organizational level, organizational climate and human resource management practices such as employee development systems and team-based rewards and training were identified as possible antecedents to team empowerment (Chen and Tesluk, 2012).
Finally, the goal-directed activities of team task performance are cyclical in nature and constantly changing (Marks, Mathieu, and Zaccaro, 2001). This episodic perspective on team tasks distinguishes between action and transition phases of team performance, with the former focusing on task engagement and the latter on task preparation and follow-up reflection. This has important leadership implications. Specifically, there are certain processes or actions that are targeted at managing the team transition phase (e.g., mission analysis, goal specification, strategy formulation and planning), other actions targeted for the action phase (e.g., monitoring progress, systems monitoring, team monitoring and backup, coordination), and actions that are relevant for both transition and action phases (e.g., conflict management, motivating and confidence building, affect management). Dynamic models of team leadership can be conceptualized in contingency or contextual leadership terms, given that different actions or leadership functions are required in different phases of team performance. Consonant with this perspective, a recent study has proposed a model of
transdisciplinary team-based research encompassing four distinct phases (Hall et al., 2012b).
Leadership and Team Faultlines
One area of research that is highly relevant to team leadership for effective team functioning is the topic of faultlines. As discussed in Chapter 4, faultlines are defined as boundaries that develop between subgroups within teams that detract from their overall effectiveness. Because faultlines escalate group conflict (Thatcher and Patel, 2012), their management, viewed within the construct of shared leadership, is essential for well-functioning teams. On the flip side, team conflict may also increase innovation by redirecting energy toward creating new ideas.
A strategy that leaders can use to mitigate subgroup conflict and strive instead toward innovation is to build superordinate team identification and superordinate goals (Bezrukova et al., 2009; Jehn and Bezrukova, 2010; Rico et al., 2012). Team identification and the strength of members’ attachment to the group may bind members together into a powerful psychological entity (Ashforth and Mael, 1989; Chao and Moon, 2005; Van der Vegt and Bunderson, 2005). Empirical research has demonstrated better performance of faultline groups when team identification is high (Bezrukova et al., 2009). Another way leaders might reinforce superordinate team identification is by establishing common goals, norms, or cultural values. Cultural misalignment between subgroup values and those of the larger business unit has negative implications for performance (Bezrukova et al., 2012). Multicultural teams may be particularly vulnerable to the development of team faultlines. Fussell and Setlock (2012) discussed types of cultural variation and the effects on teamwork, and offered several strategies for overcoming challenges presented to leaders of culturally diverse teams, including offering culture-specific and diversity awareness training for team members, developing team interaction strategies to address particular cultural issues (such as providing an anonymous way to make contributions to team discussions when some members of the team are from a culture that discourages public disagreement with leaders), and using appropriate collaboration tools.
Another approach to mitigating conflict betweeen subgroups is to create a cross-cutting strategy such as a reward system or task role assignment that cuts across the larger group (Homan et al., 2008; Rico et al., 2012). For example, in a science team or larger group, engineers and scientists may be grouped together to work on different aspects of a prototype. The crosscutting identification with the shared task would be expected to decrease bias and contribute to productive communication by reducing psychological distance between subgroups of engineers and scientists.
Finding common ground is yet another strategy that team leaders can use to leverage external conflict to make faultlines less salient. This approach unites the team to “fight” against common “enemies” outside the team (Tajfel, 1982; Brewer, 1999). In this way, the team members can perceive higher levels of team efficacy, autonomy, and relatedness, leading to increased team motivation and self-regulation (Ommundsen, Lemyre, and Abrahamsen (2010).
One area of research on leadership in business and government that may be relevant to leading science teams and larger group involves intergroup leadership. As Pittinsky and Simon (2007) discussed, leaders can encounter challenges in their efforts to foster positive relationships among subgroups of followers or constituents. Behaviors that foster subgroup or team cohesiveness can positively impact outcomes within the subgroup or team, but at a cost to relationships with other subgroups or teams, which can ultimately have a negative impact on outcomes of both the subgroups or teams and the larger business or governmental organization. This is similar to the challenge of leading multiteam systems discussed later in this chapter. Pittinsky and Simon (2007) discuss five leadership strategies for promoting positive intergroup relations: (1) encouraging contact between groups, (2) actively managing resources and interdependencies, (3) promoting superordinate identities, (4) promoting dual identities, and (5) promoting positive intergroup attitudes. Hogg, van Knippenberg, and Rast (2012) also discussed the importance of intergroup leadership and identify the leader’s ability to promote an “intergroup relational identity” (p. 233) as critical to the development of positive intergroup relationships.
In this section, we focus on the existing literature on science teams and larger groups and discuss the leadership challenges.
Models of Team Science Leadership
Because science teams and larger groups share many features with teams and groups in other contexts, their leaders can enhance effectiveness partly by facilitating the team processes shown to enhance effectiveness in other contexts, as shown in Table 6-1 above. Research and theory conducted in science contexts also suggest that leader behaviors to foster these processes will enhance effectiveness. For example, B. Gray (2008) proposed that transdisciplinary teams require leadership that creates a shared mental model or mindset among team members (i.e., cognitive tasks; see also O’Donnell and
Derry, 2005); attends to the basic structural needs of the team in terms of managing coordination and information exchange within the team and between the team and external actors (i.e., structural tasks); and also focuses on developing effective process dynamics within the team (i.e., procedural tasks).
B. Gray’s (2008) view of collaborative team science leadership is conceptually very similar to shared leadership, discussed earlier. It may be tempting therefore to conclude that effective leadership in science teams can best be accomplished by facilitating collaborative and shared leadership processes; however, this conclusion may be both premature and overly simplistic. As noted above, Hackett (2005) found that the directors of successful microbiology laboratories at elite research universities used and valued both directive, hierarchical leadership and shared, participative leadership styles. Some of these science leaders adopted permissive, participative leadership styles, allowing students and colleagues autonomy to learn and develop their own approaches, while others were more forceful in their direction and follow more sharply drawn lines of inquiry. This apparent leadership paradox is consistent with the notion that there is no one best way to lead in terms of enhancing team effectiveness. Hackett (2005) proposed that the different leadership styles reflected each director’s multiple roles as a scientist, leader, teacher, and mentor. Spending time in the laboratory may give a director greater control over technologies and subordinate scientists, but less time for writing the proposals, papers, and reviews that sustain the laboratory’s funding and its identity within the larger scientific community. Over time, many of the directors had lost their cutting-edge scientific skills and become more reliant on the work of their followers, creating new tensions of leadership.
The research suggests that team science leaders would benefit from developing skills and behaviors that would allow them to practice directive as well as more participative, collaborative, or shared styles of leadership depending on team needs. This is consistent with the dynamic leadership processes described in the previous section.
Similar to studies in other contexts showing a relationship between leader behaviors, team processes, and team effectiveness, a study of academic science teams in Europe found significant positive relationships between supervisory behavior, group climate (a team process), and research productivity (Knorr et al., 1979). Supervisory quality was measured by surveys of followers’ satisfaction, including survey items related to the supervisor’s planning functions (e.g., satisfaction with the quality of research program, satisfaction with personnel policies) and integrative functions (e.g., satisfaction with group climate, feeling of attachment to the research unit). Within the overall positive relationship between supervisory quality and group climate, ratings of the supervisors’ planning and integrative functions were the most important intervening variables.
One practical way to deal with the complexities of leading science teams or groups is through engaging the members to collectively develop a team charter, which provides a written agreement for task accomplishment and teamwork and has been shown to enhance effectiveness in teams outside of science (Mathieu and Rapp, 2009).
Emerging Team Science Models and Leadership Implications
The two models of team science described in Chapter 3 incorporate many of the leadership concepts discussed in this chapter, highlighting the potential value of professional development for team science leaders.
In their integrative capacity model, Salazar and colleagues (2012) proposed that leaders of interdisciplinary or transdisciplinary teams or larger groups can build the capacity for deep knowledge integration (one of the key features introduced in Chapter 1) through several leadership styles and behaviors. For example, leaders who use an empowering leadership style can enhance the use of the team’s intellectual resources (Kumpfer et al., 1993). This facilitates equal access to dialogue that is often hindered by status and power differences (Ridgeway, 1991; Bacharach, Bamberger, and Mundell, 1993). Building consensus through team developmental strategies such as experiential learning and appreciative inquiry, another leadership technique, can help to develop agreement around goals and problem definition, ultimately facilitating integrative knowledge creation (Stokols, 2006). Leaders who listen for places where clarification might be needed are best placed to communicate knowledge across geographic boundaries (Olson and Olson, 2000). Finally, conflict management (i.e., minimizing team divisions, as in managing the faultiness discussed above) and affect management (i.e., the facilitation of trust between team members) can serve as effective ways in which to foster collaboration and knowledge generation (Csikszentmihalyi, 1994; B. Gray, 2008; Salazar et al., 2012).
The integrative capacity model has important implications for research on team science leadership. The model’s authors are currently conducting a study to determine how the development of a team’s integrative capacity and subsequent knowledge outcomes are impacted by boundary-spanning leadership behaviors and interventions. The research has the potential to fill a vital gap within the literature by both developing measures of these constructs and empirically testing the theoretical propositions linking integrative capacity to the creation of new knowledge in multidisciplinary teams. The authors will measure the constructs and test their relationship to the theoretical propositions using a large-scale highly controlled quasi-experimental research design a sample of more than 40 interdisciplinary and transdisciplinary science teams across several U.S. universities.
The four-phase model proposed by Hall et al. (2012b) provides a roadmap to enhance the development, management, and evaluation of transdisciplinary research (see Box 3-2). It includes four relatively distinct phases: development, conceptualization, implementation, and translation and suggests the use of several tools to accomplish the goals of each phase, such as research networking tools in the development phase (see Chapter 4), the “Toolbox” seminars during the conceptualization phase (see Chapter 5), and conflict management tools during the implementation phase. This new model suggests that leaders can play a valuable role by providing the appropriate tools at each phase and working to ensure that team members use and learn from these tools.
Role of Scientific Expertise
Most leaders of science teams and larger groups are appointed or elected to these positions based on their scientific expertise (Bozeman and Boardman, 2013), and there is some evidence that subordinate scientists rate the quality of their leaders primarily in terms of such expertise (Knorr et al., 1979; Hackett, 2005). B. Gray (2008) suggested that relevant scientific expertise is critical to the leadership behaviors of managing meaning and visioning in transdisciplinary science teams or larger groups.
Leaders manage meaning for others by introducing a mental map of desired goals and the methods for achieving them while at the same time promoting individual creativity. . . . In transdisciplinary research, the cognitive tasks of leadership largely consist of visioning and framing. . . . This visioning process is referred to as intellectual stimulation by transformational leadership researchers, and includes leader behaviors that promote divergent thinking, risk taking, and challenges to established methods. Transdisciplinary leaders need to be able to envision how various disciplines may overlap in constructive ways that could generate scientific breakthroughs and new understanding in a specific problem area. They themselves need to appreciate the value of such endeavors, be able to communicate their vision to potential collaborators, and construct a climate that fosters this collaboration (2008, pp. S125–S126).
Similarly, Bennett and Gadlin (2012) proposed that effective team science leaders are able to articulate the scientific project vision, both to the research community and the home institution, in a way that allows each team member to recognize his or her contributions. Some leaders of large scientific groups have called for creating a new position, the interdisciplinary executive scientist. This role would be filled by individuals who have
both project management skills and deep expertise in at least one of the disciplinary areas involved in the interdisciplinary endeavor.3
Leadership of Multiteam Systems
A multiteam system is a complex system of teams created to accomplish goals too ambitious for any single team (Zaccaro and DeChurch, 2012). The system may consist of various types of teams and involve different leadership structures (Marks, Mathieu, and Zaccaro, 2001). In science, multiteam systems may be engaged in interdisciplinary or transdisciplinary research projects, which aim to deeply integrate knowledge from multiple disciplines and perspectives (one of the key features introduced in Chapter 1). Team leaders as well as members face the challenges emerging from this feature, as they may be unfamiliar with disciplines and perspectives included in their projects.
Of direct relevance to the seven key features that generate challenges for team science, some factors thought to be important in motivating different forms of multiteam leadership include the overall size of the multiteam system, the amount and kind of diversity, geographic dispersion, the level of interdependence among component teams, and power distribution among teams. More mature multiteam systems are reported to display greater levels of shared leadership than less mature multiteam systems, which makes sense given that shared leadership takes time to develop (DeRue, 2011). An example of this evolution, described further in Box 6-1, is the shared leadership within the large multiteam system of physicists, engineers, and computer scientists conducting research enabled by the Large Hadron Collider in Switzerland. The development of this shared leadership approach within what has been described as a “communitarian culture” in particle physics was born of necessity, because the funding level required for such large facilities precludes funding similar projects in multiple locations. In light of the growth of multiteam systems, other disciplines than particle physics might benefit from a similar philosophy and leadership approach.
In multiteam systems, leaders can engage participants in developing charters as a way to develop effective norms for between-team communication and leadership processes (Asencio et al., 2012). The process of creating a charter can also be used to identify a representative from each team who would participate in system-level leadership, help coordinate multiteam actions, and convey information across team boundaries.
To date there has been relatively little empirical research on leadership in multiteam systems. One study involved analyses of critical incidents in
3 See https://www.teamsciencetoolkit.cancer.gov/Public/expertBlog.aspx?tid=4&rid=1838 [April 2015] for further discussion of this proposed position.
mission-critical multiteam environments, such as disaster relief systems (DeChurch et al., 2011). Based on the analysis, the authors identified a set of leadership behaviors that promoted positive team and interteam processes and enhanced performance of the multiteam systems. These behaviors included formulating overall strategy and coordinating the activities of the component teams. In a laboratory study examining leadership functions hypothesized to be important in synchronizing multiteam systems, DeChurch and Marks (2006) manipulated leader strategizing and coordinating and assessed their effects on functional leadership, interteam coordination, and the performance of the multiteam system. Results supported a multilevel (i.e., team and multiteam) model in which leader training positively influenced functional leadership, which in turn improved inter-team coordination, and ultimately resulted in improved performance of the multiteam system.
Leader and team member skills and knowledge are essential to foster effective team science. This includes both scientific knowledge and skills relevant to the research problem at hand and knowledge and skills to foster positive team or group processes that, in turn, enhance scientific effectiveness. The previous chapter discussed education and professional development for team members. Here we discuss approaches to developing the skills and knowledge required for effective leadership of science teams and larger groups.
Research conducted in contexts outside science has found that formal leadership development interventions can help leaders develop the capacity to foster positive team and organizational processes, thereby increasing team or organizational effectiveness (e.g., Avolio et al., 2009; Collins and Holton, 2004). For example, in a meta-analysis of research on leadership and performance, Avolio et al. (2009) found, across 37 leadership training and development interventions, a positive corrected effect size (d) of .60. The authors also analyzed the return on investments in the training and development interventions included in the study. They found that investments in the interventions with moderate to strong effects would yield positive returns in improved performance. For example, for a mid-level leader, the return on an investment in a development intervention with moderate effects ranged from 36 percent for online training to 169 percent for on-site training. As noted above, in their laboratory study of multiteam system leadership, DeChurch and Marks (2006) found that leader training positively influenced functional leadership, which in turn improved interteam coordination, thereby improving the performance of the multiteam system.
CERN: An Example of Successful Multiteam System Leadership
On July 4, 2012, the European Organization for Nuclear Research, also known as CERN, in Geneva, Switzerland, announced the observation of a new subatomic particle consistent with the Higgs boson. Described as the “Holy Grail” of physics, the Higgs boson is important to fundamental understanding of the universe because it helps to explain why matter has mass. The CERN laboratory, founded in 1954, includes the Large Hadron Collider and detectors built specifically to study the Higgs mechanism. The observation of the Higgs boson was announced by two groups made up of thousands of physicists, engineers, computer scientists, and technicians from around the world (ATLAS Collaboration, 2012; CMS Collaboration, 2012). Research to date suggests that the unique organizational structures (Shrum, Genuth, and Chompalov, 2007) and culture (Traweek, 1988; Knorr-Cetina, 1999) of particle physics contributed to this scientific breakthrough.
Following World War II, as physics developed into an important research field, investigators developed increasingly large and powerful particle accelerators and detectors to measure the activity of the particles. Groups organized around detectors functioned as semi-autonomous units, linked to others by exchanges of information, students, postdoctoral fellows, and technical gossip (Traweek, 1988). At CERN, the two groups that discovered the Higgs boson are referred to as “experiments” and are named for the detectors that are the focus of their research—the Compact Muon Solenoid (CMS) and ATLAS detectors—located within the Large Hadron Collider. Each experiment is a very large group within the CERN system, and each is composed of multiple layers of groups and subteams. This organizational structure reflects DeChurch and Zacarro’s (2013) model of a multiteam system—an organization made up of multiple teams that work toward different team goals, but share at least one system-level goal.
DeChurch and Zaccaro (2013) propose that multiteam systems must balance the tensions of confluent and countervailing forces to succeed. Confluent forces, such as coordination within and across teams, combine across teams and jointly enhance the performance of the entire system. Countervailing forces, in contrast, operate in contradictory ways within and across teams, detracting from the performance of the entire system. For example, team cohesion and strong feelings of unique team identity may enhance team-level performance but compromise information-sharing across teams.
The CMS experiment (Incandela, 2013) includes approximately 4,300 scientists, engineers, and technicians from 42 countries and 190 institutions. Participants work in hundreds of subteams organized in two major categories: service and physics. The service category includes, for instance, a computing team that manages more than 100,000 computers in 34 countries and an offline team that manages reconstruction and analysis software. These teams collect petabytes of information (22 in 2011 and 30 in 2012) for analysis, and oversee the networking and computational resources to allow distributed access, called the grid. The physics category includes multiple groups, such as the Higgs group of approximately 700 physicists organized into five subteams (Incandela, 2013).
Both egalitarian and hierarchical, the experiment is led by consensus among physicists motivated both by common interests and by formal goals and decisions established by CERN and experiment leaders.* At the top level are a board with representatives of all of the collaborating national research institutions and an elected spokesperson who is the executive head of the experiment. Countervailing forces sometimes emerge from strong identification with a subteam or subgroup, usually because an overly ambitious subteam leader has difficulty with collaborative science. To address this, top leaders rotate subteam leaders every 2 years, often appoint two co-leaders, and, if there is potential danger to the entire experiment (the system level), they may intervene as a last resort to replace a problematic subteam leader. Countervailing forces are also dampened by the general approach of drawing subteam leaders from within the team. If they demonstrate excellent performance, they may have more influence when they return to the team, or they may be promoted—a possibility that may motivate them to maintain cohesion with other teams in pursuit of the higher-level goals of CMS.
To encourage confluent forces, CMS leaders engage in intense, ongoing, and transparent communications. They convene collaborationwide weekly meetings to discuss news, challenges, strategies, and plans. Almost all meetings are open to any participant (who may attend in person or by videoconference), and open discussion of any major shifts in strategy encourages all subteams to focus on systemwide goals.
At the same time, CERN leaders have worked to mitigate conflicts or countervailing forces between and within the two experiments. For example, in the early development of ATLAS, leaders used a slow, deliberative process to avoid conflicts between potential groups of participants. Through extensive consultation, they were able to break open established, and often competing, research groups and bring them into the project, as well as U.S. physicists who had been engaged in design and planning of the Superconducting Super-Collider (SSC), a project that was stopped by the U.S. Congress in 1993.
Particle physics has a unique “communitarian” culture, where verbal communication is of great importance and people meet frequently at large and small conferences and quickly disseminate information to each other (Knorr-Cetina, 1999). This culture encourages scientists to work for the common good. For example, the two papers announcing the discovery of the Higgs boson were authored by the “ATLAS Experiment” and the “CMS Experiment.” An online appendix listed the 2,891 co-authors of the CMS paper, in alphabetical order, including all who contributed to any part of designing, building, operating, or analyzing data from the experiment. These publications reflect the established rule that any results are owned by the collaboration. Individuals cannot publish results before going through the regular process of review and approval inside the experiment, with input from the CERN publications committee. This internal review process is so thorough that journals trust the outcome with little further review—a practical solution since most of those with the technical expertise to serve as journal peer reviewers are affiliated with the experiments.
*Because most funding for CERN experiments is controlled by member institutions and nations rather than CERN directly, laboratory leaders rely heavily on consensus building to achieve their goals (Hofer et al., 2008).
Leadership development trajectories are influenced not only by formal training and leadership development programs, but also by experience in leadership positions. Day (2010) noted that deliberate practice is a very important component of leadership development, as is fostering a sense of identity as a leader, which can lead to greater interesting in learning about leadership and improving leadership skills (see Day, Sin, and Chen, 2004; Day and Harrison, 2007; Day, 2011; Day and Sin, 2011). In addition to the mechanisms of formal training programs and experiential learning, self-directed learning or self-development can play an important role in leadership development (see Boyce, Zaccaro, and Wisecarver  for an examination of leaders’ propensity for self-development). Formal leadership training interventions may work to improve leadership styles and behaviors partly by fostering participants’ sense of identity as a leader, and thus supporting experiential and self-directed learning.
The scientific community has begun to recognize the potential benefit of formal professional development for team or group leaders. Efforts are under way to extend and translate the leadership research to science contexts, as briefly described in the examples below.
Science Executive Education
This program funded by the National Science Foundation (NSF) is designed to address the fact that science executives who manage science enterprises often learn on-the-job through trial and error, usually without benefit of knowledge from organization science that might help them. As is the case for business executives, science executives need expertise in organizational governance, innovation management, resource provisioning, workforce development, turnover reduction, process improvement, and strategic leadership. However, for important contextual reasons, such as the fact that the business focus is on competitive industries rather than the pre-competitive world of basic research, business education models usually cannot be directly applied to science. Science executives increasingly have to balance long-term versus short-term goals, temporary projects versus permanent organizations, planning versus spontaneous action, and standardization versus fluid technical innovation. Hence, the lack of science executive expertise is regarded as a “rate-limiter” to moving toward greater coordination and collaboration.
In response to this need, the Science Executive Education Program was developed, drawing on research on interorganizational governance, virtual teams, distributed team collaboration, and innovation management involving organizational learning and memory. Extending project management to entrepreneurial leadership is at the center of science executive education (Cummings and Keisler, 2007, 2011; Karasti, Baker, and Millerant, 2010; Claggett and Berente 2012; Rubleske and Berente, 2012). Science executive
education focuses on four main areas: matching sources and uses for funds over time, explaining the “value-added” of centers to various constituencies, improving hiring and retention of key employees, and better handling of the “socio” in socio-technical systems.
Project Science Workshops
This program, which has been in existence for 11 years, aims to develop project management skills for leaders of large scientific research projects. Developed by astronomer Gary Sanders with support from NSF, the annual workshop uses didactic presentations and case studies to cover a range of project management challenges, including design of complex projects and the tools needed for their management.4 Topics at the workshop have included large-scale collaborative science; building scientific structure and partnerships; and selection, governance, and management of unique large-scale research facilities. The 2012 workshop attracted scientists from a wide range of large projects, such as the Blue Waters supercomputer at the University of Illinois at Urbana–Champaign, the Summit Station Greenland facilities, the iPlant collaborative focused on creating cyber infrastructure and tools for plant biology, and the interdisciplinary team creating the Thirty Meter Telescope in Pasadena, California.
Leadership for Innovative Team Science (LITeS)
The Colorado Clinical and Translational Sciences Institute (CCTSI) developed the LITeS Program in 2008 to strengthen participants’ leadership, to foster team science through the establishment of a network of researchers who can support one another, and to increase opportunities for researchers to collaborate across disciplines. The program is provided annually to a cohort of both senior and developing leaders working in clinical and translational research at the University of Colorado, and is structured as a full-year experience that includes participation in small-group projects and four workshops covering a variety of topics relevant to science team leadership, as well as individual feedback and coaching (Colorado Clinical and Translational Sciences Institute, 2014). The program description on the institute’s website (Colorado Clinical and Translational Sciences Institute, 2014, p. 6) states that the LITeS Program “is designed to address three major domains for leadership: (1) knowledge of individual leadership styles and behaviors; (2) interpersonal and team skills for leading, managing, and working with people; and (3) process skills for increasing quality and efficiency in the work of academic leadership.”
The research findings on the general topic of leadership, team leadership, and science teams in particular address the challenges of team science in unique ways. The consistent theme from this research is that no single leadership style or behavior can be prescribed for effective leadership and management of science teams, but rather, a combination of approaches is required. This combination encompasses: shared and hierarchical leadership; contingency and dynamic leadership that recognize the cyclical and temporal needs of a team as it develops and evolves over time; goal alignment; and the management of faultlines within and between teams that manifest as conflict, including conflict that drives innovation. Moreover, emerging research suggests that leaders of science teams and larger groups can be helped to acquire leadership behaviors and management skills. In Table 6-2, we summarize how the research findings discussed in the previous section might be applied to address each of the team science features that can create communication and coordination challenges.
Currently, most leaders of science teams and larger groups are appointed to their positions based solely on scientific expertise and lack formal leadership training. At the same time, an extensive body of research on organizational and team leadership in contexts outside of science has illuminated leadership styles and behaviors that foster positive interpersonal processes, thereby enhancing organizational and team performance. Extending and translating this research could inform the creation of research-based leadership development programs for leaders of science teams and groups. The committee expects that such programs would strengthen science team leaders’ capacity to guide and facilitate the team processes, thereby enhancing team effectiveness.
CONCLUSION. Fifty years of research on team and organizational leadership in contexts other than science provide a robust foundation of evidence to guide professional development for leaders of science teams and larger groups.
RECOMMENDATION 3: Leadership researchers, universities, and leaders of team science projects should partner to translate and extend the leadership literature to create and evaluate science leadership development opportunities for team science leaders and funding agency program officers.
TABLE 6-2 Addressing Seven Features That Create Challenges for Team Science
|Feature||Leadership Research Addressing the Challenges Emerging from the Feature|
|1. High Diversity of Membership||
|2. Deep Knowledge Integration||
|3. Large Size||
|4. Goal Misalignment with Other Teams||
|5. Permeable Team and Group Boundaries||
|6. Geographic Dispersion||
|7. High Task Interdependence||