Team Dispersion and Performance: The Role of Team Communication and Transformational Leadership

Abstract

Organizations increasingly rely on virtual teams to access geographically dispersed expertise. Yet, team dispersion introduces challenges to team communication that may negatively influence team performance. Using a sample of 53 innovation teams representing a variety of geographic dispersion configurations from completely collocated to highly dispersed, we examined the moderating role of transformational leadership on the relationship between team dispersion, team communication, and team performance. Our findings suggest that while transformational leadership is effective in reducing the negative effects of dispersion in collocated teams or ones with low levels of geographic dispersion, it is less effective helping improve the performance of highly dispersed teams. This effect may be due to a transformational leader’s difficulty in facilitating team communication in highly dispersed teams, where his or her influence might actually have counterproductive effects. We discuss the implications of our findings for theory, future research, and practice.

Keywords

virtual groups leadership communication teamwork

Advances in technology and the need to access expertise from around the world (Gibson & Gibbs, 2006) have led to a steadily growing reliance on geographically dispersed or virtual teams in modern organizations (e.g., Dulebohn & Hoch, 2017; Kratzer, Leenders, & Van Engelen, 2006; Marlow, Lacerenza, & Salas, 2017), especially in research and development (R&D) environments (Andres, 2002; Boutellier, Gassman, Macho, & Roux, 1998; Kratzer et al., 2006). Accessing the expertise required for achieving complex tasks, such as innovation, frequently necessitates collaboration of team members across geographically dispersed office locations. As organizations increasingly rely on geographically dispersed teams, despite their challenges, it is important to understand factors that influence their team performance.

Despite continuous improvements in communication technology, employees’ geographical dispersion remains a challenge to effective workplace interactions and, particularly, to teamwork (Han & Beyerlein, 2016; Walther & Bunz, 2005; Z. Wang, Walther, & Hancock, 2009). Geographically dispersed or virtual teams are groups of people who share common goals and who collaborate on interdependent tasks across distance and time, using a variety of information technologies (Ebrahim, Ahmed, & Taha, 2009; Kirkman & Mathieu, 2005; Lipnack & Stamps, 1997). In this article, we conceive of team geographic dispersion as a continuum representing the extent to which a team’s members participate from a wider variety of locations, with low dispersion representing a team that is entirely or mostly collocated and high dispersion indicating a team whose members each work in separate locations. As a team’s geographic dispersion increases, the more difficult it is for team members to have periodic face-to-face gatherings that might facilitate their collaboration and rapport. Few teams nowadays work completely face to face, which is why studying teams on a continuum from collocated to greatly geographically dispersed is timely.

Geographically dispersed teams are increasingly common in modern organizations and, therefore, receive much attention in the research literature (e.g., Charlier, Stewart, Greco, & Reeves, 2016; Dulebohn & Hoch, 2017; Marlow et al., 2017). A team’s geographic dispersion affects its members’ interactions because greater dispersion among team members tends to be associated with a greater variety of different norms across their environments, which may diminish team members’ ability to trust and understand each other, and impede the effectiveness or their communication and collaboration.

Empirical studies on the relationship between team dispersion and team performance show mixed results (see, for example, Kratzer et al., 2006; Maynard, Mathieu, Rapp, & Gilson, 2012). On one hand, geographically dispersed teams face a number of unique challenges that hinder their performance (e.g., Hardin, Fuller, & Davison, 2007; McLeod, 2013; Perry, Lorinkova, Hunter, Hubbard, & Mcmahon, 2016), among which team communication looms large (Hertel, Geister, & Konradt, 2005; Marlow et al., 2017). On the other hand, a team’s geographic dispersion may provide access to expertise regardless of their location, which may enhance team performance, especially for teams focusing on complex tasks (Ebrahim et al., 2009).

The mixed results about the effects of teams’ geographic dispersion on their performance suggest that the impact of a team’s geographic dispersion on its performance may depend on how such dispersion is managed (Kratzer et al., 2006), together with the extent to which members are dispersed (Kirkman & Mathieu, 2005). Effective leadership of geographically dispersed teams is crucial in addressing the challenges associated with the dispersed environment and in influencing team processes and outcomes (e.g., Bell & Kozlowski, 2002; Kayworth & Leidner, 2002; Liao, 2017). Therefore, given the importance of leadership in this context, the study of leadership styles as moderators of the team dispersion–team performance relationship seems especially promising (Hambley & Kline, 2007; Hambley, O’Neill, & Kline, 2007; Mathieu, Maynard, Rapp, & Gilson, 2008).

In this study, we examine the role of transformational leadership in moderating the influence of team geographic dispersion on the performance of innovation teams. Transformational leadership is especially appropriate for three important reasons. First, transformational leadership is one of the styles that has received attention in the literature on virtual teams but with divergent findings (Balthazard, Waldman, & Warren, 2009; Gilson, Maynard, Jones Young, Vartiainen, & Hakonen, 2015; Hambley & Kline, 2007), as is discussed below. Despite some criticisms ranging from the dependency on followers and the negative connotation for leaders themselves (Lin, Scott, & Matta, 2018), to lack of sufficient evidence about moderating influences (van Knippenberg & Sitkin, 2013), transformational leadership has overwhelmingly received praise in the literature. It has been associated with idealized influence, inspirational motivation, individualized consideration, and intellectual stimulation behaviors (Bass & Avolio, 1994) and has largely been recognized for its positive influence on team processes and performance for many years and across numerous studies for inspiring followers to go above and beyond in accomplishing goals (e.g., Braun, Peus, Weisweiler, & Frey, 2013; Dionne, Yammarino, Atwater, & Spangler, 2004; Lowe, Kroeck, & Sivasubramaniam, 1996). Second, transformational leadership appears to be especially helpful for teams working on such complex tasks as innovation. It has been recognized as a “driver of change and creativity” (Li, Mitchell, & Boyle, 2016, p. 67) and is associated with goal creation, inspiration, and high levels of follower motivation (Price, 2003). It has also been demonstrated to have positive effects on virtual teams focused on creativity-related tasks (Purvanova & Bono, 2009). Thus, transformational leadership is an appropriate focus for our study of innovation teams with dispersed members. Third, and paradoxically, team members may increasingly perceive their transformational team leader to be inauthentic because moral identities and values are expected to vary as a team’s geographical dispersion increases (e.g., Bass & Steidlmeier, 1999; Price, 2003; Zhu, Avolio, Riggio, & Sosik, 2011). Such perceptions may diminish the effectiveness of transformational leadership in dispersed teams.

Both geographic dispersion and transformational leadership shape team performance by influencing critical intermediary processes (Avolio, Walumbwa, & Weber, 2009), such as team communication. Numerous studies over the years have not only highlighted the vital importance of team communication for geographically dispersed teamwork (e.g., Charlier et al., 2016; Leenders, van Engelen, & Kratzer, 2003; Marlow et al., 2017) but also noted the communication problems associated with dispersed teamwork. Specifically, these studies show that virtual team settings hinder team communication and, in turn, team performance for a variety of reasons, ranging from a reduced opportunity for members to develop trustworthy relationships to an inability of members to collaborate concurrently due to time zone differences. Without effective communication, teams are likely to have a harder time exchanging depth of knowledge and ideas necessary for greater team performance.

Leaders influence team members through various communication-related processes. However, communication may be particularly challenging in a dispersed environment, negatively affecting a leader’s overall influence on the team. The increasing challenges and complexity resulting in the negative influence of geographical dispersion of team members on their team performance has been well established in the literature (Ferreira, de Lima, & da Costa, 2012; Hinds & Bailey, 2003; Martins, Gilson, & Maynard, 2004). Thus, our focus is on examining the effects of a well-known and overall effective leadership style, transformational leadership, as a way of reducing the negative effects of dispersion on team communication and performance. We propose and test a model of the team dispersion–team performance relationship, moderated by transformational leadership and mediated by team communication. The model is illustrated in Figure 1.

Figure 1.

Theoretical model.

Our study offers three distinct contributions and, in doing so, addresses several shortcomings in the literatures on geographically dispersed teams and leadership. First, we contribute to these literatures by explicitly modeling and testing how transformational leadership interacts with team dispersion to influence team performance both directly and indirectly, through team communication. As such, our study evaluates not just whether transformational leadership influences the performance of geographically dispersed teams but also how it does so in teams with a variety of distribution types. Second, we use field data, that is, data from organizational members rather than from students. Extant research, using experimental designs and samples comprised of undergraduate students rather than industry workers, while highly useful in exploring the possible effects of team leadership on communication and performance, may be insufficient to capture the durable effect of a leadership style as it interacts with team dispersion to influence performance in established work teams (Hambley et al., 2007). Third, we use a research design that allows for a wide range of team dispersion. In contrast, extant experimental designs often compare completely collocated teams (i.e., teams in which all members work face to face in the same location) with completely dispersed teams (i.e., teams in which none of the members has met another member face to face). Our research design more accurately captures the nature of team dispersion in modern work organizations than previous designs and, thus, our study can be more broadly generalized to actual workplace teams. Although there is ample research on how transformational leadership may facilitate team performance, the research is scant on its effects across different levels of geographical dispersion of a team (Hambley & Kline, 2007). The extent of geographical dispersion, among other types of team configurations (Gibson & Gibbs, 2006), has important implications on how a team operates.

Given the increasing prevalence of geographically dispersed teams (Dulebohn & Hoch, 2017), it is crucial to evaluate how some of the popular approaches to addressing teamwork challenges, such as transformational leadership, apply to dispersed teams. In this study, we focused on the moderating role of transformational leadership on the team dispersion–team performance relationship because of its predominantly positive association with leadership effectiveness (Lowe et al., 1996) and team performance (Dionne et al., 2004), including its effects in virtual teams. Transformational leadership has been found to have beneficial effects, and managers consider it to be a highly desirable leadership style, despite research suggesting that there are boundaries to its effectiveness (Howell, Neufeld, & Avolio, 2005; Pawar & Eastman, 1997) and that it even has a dark side (Lin et al., 2018; Tourish, 2013). For example, some scholars have pointed to organizational structure (e.g., centrality and formalization) as boundary conditions to the effectiveness of transformational leadership (Walter & Bruch, 2010). Given the increasing reliance of organizations on geographically dispersed teams, improving our understanding of the role that transformational leadership has in facilitating communication and in turn performance in dispersed teams is timely.

Transformational Leadership

Moderator of the Team Dispersion–Team Performance Relationship

Transformational leadership is a leadership style that motivates followers to achieve higher levels of team performance (Dvir, Eden, Avolio, & Shamir, 2002). The leader behaviors associated with transformational leadership—idealized influence, inspirational motivation, individual consideration, and intellectual stimulation—transform followers, enable them to reach their potential, and achieve maximum levels of performance (Dvir et al., 2002). For example, transformational leaders may improve team outcomes by helping to raise team members’ beliefs in the effectiveness of their work, by expressing expectations of high team performance (Sosik, Avolio, Kahai, & Jung, 1998), and by providing individualized consideration to members through individual development opportunities (Dionne et al., 2004). In a sense, transformational leadership goes above and beyond transactional leadership, among other leadership styles and, as such, is likely to have a more positive influence on geographically dispersed team interactions (Hoyt & Blascovich, 2003) and, therefore, on team performance (G. Wang, Oh, Courtright, & Colbert, 2011).

Geographically dispersed team environments present a number of issues that negatively influence team performance. These issues range from lack of personal ties to collaboration-related problems to leadership challenges (Gilson et al., 2015; Ortiz de Guinea, Webster, & Staples, 2012; Wax, DeChurch, & Contractor, 2017). Greater team dispersion presents additional hindrances to team performance because distance, time, culture, and multiple other boundaries restrict the opportunities for quality interactions and hinder team members’ abilities to cultivate interpersonal relationships. As a team’s geographic dispersion increases, so does the number of team members whose relationships and interactions are adversely affected and, increasingly, present a hindrance to team performance.

For transformational leadership to be effective, it must be grounded in moral foundations and followers need to perceive it as authentic (e.g., Bass & Riggio, 2006; Price, 2003; Zhu et al., 2011). We argue that, as dispersion increases, the positive influence of transformational leadership on performance decreases, because members of more geographically dispersed teams will increasingly doubt leaders’ transformational leadership behaviors (idealized influence, inspirational motivation, individualized consideration, and intellectual stimulation) as being authentic.

First, geographic dispersion weakens the perceived authenticity of idealized influence, because effectively communicating such enthusiasm requires personal, often nonverbal, face-to-face interactions with followers (Bass, 1985; Podsakoff, MacKenzie, Moorman, & Fetter, 1990; Shamir, House, & Arthur, 1993). Team geographic dispersion also weakens the perceived authenticity of idealized influence, because transformational leaders, who tend to appeal to team members on an emotional level, relying on social influence and emotional contagion that create synergy between members (G. Wang et al., 2011), have fewer opportunities for creating synergies as members are increasingly dispersed across a wider array of locations. Finally, team geographic dispersion weakens the perceived authenticity of a transformational leader’s idealized influence, because exerting idealized influence requires common moral foundations between leaders and followers (Bass & Steidlmeier, 1999), which is more difficult as members of a team are increasingly separated from each other geographically (Bass & Steidlmeier, 1999).

Second, geographic dispersion weakens the perceived authenticity of inspirational motivation because, with members increasingly dispersed among a wider variety of locations, members and leaders are less likely to share values, norms of behavior, and mental schema (Hinds & Bailey, 2003; Price, 2003), and followers may therefore question the authenticity of leaders when the leader’s inspirational values and motivational language are not aligned with those of the followers (Bass & Steidlmeier, 1999). In support of this claim, other studies have shown that receivers of inspirational messages construe them to be increasingly inauthentic as the physical distance between the message sender and the receiver increases (Grant & Hofmann, 2011; Yammarino, 1994), perhaps because followers perceive such efforts, aimed at their “most private values, attitudes and aspirations” (Tourish, 2013, p. 20) to be intrusive.

Third, geographic dispersion weakens the perceived authenticity of individualized consideration, because in more dispersed teams, leader–follower relationships tend to be impersonal (Howell & Hall-Merenda, 1999), and members who are more geographically distant tend to be less trusting of leaders’ interest in their needs and desires (Zigurs, 2003). As a team’s geographic dispersion increases, it also becomes more difficult for leaders to develop the kinds of personal, close, and continuous contact with followers that are required for effective individualized consideration (Bass, 1985; House, Spangler, & Woycke, 1991; Podsakoff et al., 1990). Supporting our rationale, Bell and Kozlowski (2002) show that mentoring is less effective in geographically dispersed (compared with collocated) teams, because of the lack of close relationship between mentor and mentee.

Fourth, geographical dispersion weakens the perceived authenticity of intellectual stimulation because, as dispersion increases, it progressively hampers leaders’ ability to assess a team’s situation, identify which team members’ assumptions may need to be challenged, ask the right questions, or initiate interventions to intellectually stimulate all team members (Avolio et al., 2001; Latham & Ernst, 2006). Given the growing difficulty because of dispersion of correctly assessing the team’s circumstances, knowledge, and resources, transformational leaders’ intellectual stimulation efforts, such as challenging the status quo, are likely to become increasingly misplaced and, therefore, ineffective.

Although the use of information technology can help mitigate the problems of geographical dispersion, it is only recently that such technologies have become of sufficient quality to substitute for face-to-face interactions. Yet, paradoxically perhaps, technologies intended to substitute for face-to-face interactions may also cause more disengagement (Gibbs, Rozaidi, & Eisenberg, 2013). Furthermore, they are not always reliable. And, even when they are, such interactions are still only periodic, even more so when people are separated by time zones.

Given the above considerations, we posit that transformational leadership will not have a consistently positive effect on the relationship between geographical dispersion and team performance:

Hypothesis 1: Transformational leadership moderates the relationship between team dispersion and team performance. In teams with low levels of geographic dispersion, transformational leadership will reduce the negative effects of dispersion on team performance to a greater extent than in highly dispersed teams.

Moderator of the Team Dispersion–Team Communication Relationship

Recently, team communication in dispersed teams has been identified as a key factor in team performance (Marlow et al., 2017). Earlier studies have found that communication among team members coupled with a transformational leader are important factors that influence team performance (Dionne et al., 2004). Transformational leadership may also facilitate communication in teams with low or no geographical distribution (Boerner, Eisenbeiss, & Griesser, 2007). However, while transformational leadership is usually lauded for its positive effects on teamwork, there may be boundaries to how much transformational leadership can improve team communication, and in turn, team performance across various levels of geographic dispersion. This may be especially true in highly dispersed teams.

Transformational leadership influences followers by appealing to their individuality and by using verbal as well as nonverbal communication (Rafferty & Griffin, 2004; Shamir et al., 1993), but this approach may be less effective in teams characterized by high levels of geographical dispersion (Cramton, 2001; Powell, Piccoli, & Ives, 2004). While the negative effects of geographic dispersion on team performance should be mitigated by the use of a transformational leadership approach, it is unlikely that transformational leaders will be as effective with team members with whom they do not have a close bond due to geographical distance. In highly geographically dispersed teams, transformational leadership is likely to have less of an influence in eliciting a high level of team communication for multiple reasons. Communication may be hindered due to the difficulty in the leader being able to exert the type of influence associated with transformational leadership. For example, transformational leaders, by engaging in close and continuous contact with team members, are able to provide individualized consideration (Bass, 1985; House et al., 1991; Podsakoff et al., 1990). That is harder to accomplish in dispersed teams.

Electronically mediated communication is often used to complement, supplement, or even substitute face-to-face communication in dispersed teams, but it is still not as effective as face-to-face communication in fostering the process of building bonds (Jarvenpaa & Leidner, 1999) and in facilitating information exchanges and collaboration among team members (Ahuja & Galvin, 2003). This is in part due to reduced interactional cues and a different way in which members share socioemotional messages across information and communication technologies (Yilmaz & Youngreen, 2016). Studies show that distance creates communication barriers and is associated with less efficient and less frequent communication among members (Cordery & Soo, 2008; Van den Bulte & Moenaert, 1998). Therefore, we expect that leaders of dispersed teams have less time to spend with more distant team members and that their contact with such members will suffer from interruptions even if the leaders periodically visit the geographic sites where the team members are located. Being removed from their leaders may make dispersed team members feel less valued, possibly resulting in feelings of resentment that can explain some of the communication-related challenges frequently reported in geographically dispersed teams (Kirkman & Mathieu, 2005). Furthermore, dispersed team members may find it hard to fully embrace their team’s transformational leader. It, therefore, appears that in highly dispersed teams, a greater effort to use transformational leadership may not be as effective as would otherwise be expected in addressing the communication problems that are frequently associated with highly dispersed teams.

In sum, transformational leaders’ effectiveness is based on providing idealized influence, inspirational motivation, individualized consideration, and intellectual stimulation. As such, their leadership style will be more effective in collocated teams and will be more effective in mitigating the negative effects of dispersion on communication in teams with a low level of dispersion and less effective in addressing the negative effects of highly geographically dispersed teams, where opportunities to establish personalized relationships are likely to be significantly lower. Thus, we posit the following hypothesis:

Hypothesis 2: Transformational leadership moderates the relationship between geographic team dispersion and team communication. Specifically, in teams with low levels of geographic dispersion, transformational leadership will reduce the negative effects of dispersion on team communication to a greater extent than in highly dispersed teams.

Team Communication

Mediator of the Moderating Effect of Transformational Leadership on the Team Dispersion–Team Performance Relationship

To achieve higher performance levels, teams rely extensively on open and prompt communication (e.g., Ancona & Caldwell, 1992; Dionne et al., 2004). Interpersonal relationships are affected by types of computer-mediated communication (Walther, 1995). In a quasi-experimental study of students, greater reliance on rules and norms of communication helped team members work better together in distributed teams (Walther & Bunz, 2005). However, such conditions are quite unrealistic for industry work teams focusing on complex tasks, such as innovation, which require novel approaches and going outside the norms to create solutions. Thus, geographical distribution of team members is likely to hinder team communication in industry teams, negatively influencing their interactions. Furthermore, difficulties associated with establishing trust, which is likely to be harder in distributed teams, due to reduced cues available in computer-mediated exchanges, may make communication more complex (Jarvenpaa & Leidner, 1999). Improving perceptions of communication effectiveness had a positive effect on quality of decision making and performance of face-to-face and geographically dispersed teams (Chidambaram & Jones, 1993).

Overall, among more geographically dispersed teams, effective communication has been acknowledged to be a critical determinant of team performance (Foster, Abbey, Callow, Zu, & Wilbon, 2015; Marlow et al., 2017; Powell et al., 2004). For example, on geographically dispersed engineering teams, effective communication led to improved quality, reduced costs, and faster turnaround for new products (May & Carter, 2001). Improving the effectiveness of skills related to computer-mediated communication enhanced relational links and information exchange in virtual teams (Warkentin & Beranek, 1999). Quality of team communication–related processes, in computer-mediated environments, has influenced task performance (Dennis, Fuller, & Valacich, 2008).

Informal and spontaneous communication are important for improving team functioning in geographically distributed teams (Hinds & Mortensen, 2005), and may require a leader’s involvement to help facilitate it. Furthermore, the leader may help to understand and address communication challenges associated with the members having differing assumptions, norms, and constraints related to work in geographically dispersed teams (Thatcher & Patel, 2011).

Team dispersion is associated with challenges to effective communication (Cramton, 2001; Powell et al., 2004), reduced trust (Zigurs, 2003), confidence in their ability to perform (Hardin et al., 2007), and decreased implicit knowledge transfer (Reed & Knight, 2010), all of which make it difficult for transformational leaders to influence team members and motivate them to strive for high team performance. Drawing on research which finds that, among collocated teams, communication appears to interact with the effects of transformational leadership on performance (Smith, Arthur, Hardy, Callow, & Williams, 2013), coupled with research highlighting the key role of communication in geographically dispersed teams, we anticipate that the effect of the interaction of team dispersion and transformational leadership on team performance will be mediated by team communication. Thus, we hypothesize the following:

Hypothesis 3: Team communication mediates the moderating effect of transformational leadership on the geographic team dispersion–team performance relationship.

Method

Sample

Member companies of the Industrial Research Institute (IRI), a major professional association representing more than 200 industrial R&D companies, volunteered 55 innovation teams, which had participated in a broader research project, including a pilot study, to take part in our online survey. The teams were cross-functional, tasked with various innovation-focused work, such as developing new consumer goods. The projects required mutual learning, coordination, and close collaboration among team members. The teams had been working together for a minimum of 3 months and were still working together or had been disbanded less than 60 days prior to the start of our study. For all of the teams, we had information about each member’s geographic office location. We excluded two teams because of missing data. The remaining 53 teams, comprising 543 individual team members, constitute our sample. Each team member responded to a 30-min online survey. On average, 94% of the teams’ members responded to the survey.

We collected performance-related data from team members and stakeholders. Stakeholders were executives from the senior ranks of their organizations, not part of the team but having an interest in and sufficient involvement with the team in question to enable them to fairly evaluate the team’s performance. We collected data from both team members and stakeholders to avoid the methodological problems associated with having a single source of data (Lindell & Whitney, 2001). We administered the stakeholder and the team member surveys concurrently, and both were confidential. For each team, we surveyed two or three stakeholders. We received responses from more than 90% of the stakeholders. Survey question responses ranged from 1 = strongly disagree to 7 = strongly agree, unless indicated otherwise.

Measures

Team performance (stakeholder evaluations)

The stakeholders for each team rated their respective team’s performance. The stakeholder performance measure is based on four items (α = .74) that were used in earlier work (Edmondson, 1999; Hackman, 2002) as well as from our analysis of interviews in a pilot study. The items asked about the team’s ability to successfully carry out its plans, the number of issues the team generated, whether the issues required escalation to management, and the stakeholders’ perceptions of their respective teams. The responses provided an outsider’s perspective of the teams’ performance. We aggregated the individual stakeholder responses to the team level by averaging the responses into a team-level measure of performance. The low average number of stakeholders who responded to the survey (2-3) prevented us from conducting similarity and reliability analyses to assess agreement among stakeholders for each team.

Team performance (team member evaluations)

Team members for each team rated their respective team’s performance. The team member performance measure is based on eight items (α = .90) that were used in earlier studies (Edmondson, 1999; Hackman, 2002) and on interviews we conducted during the pilot study. The items asked about the team’s performance relative to the team’s own expectations and relative to stakeholder’s expectations, for an evaluation of their team innovativeness, timeliness, and norms of interaction. We aggregated the individual team member responses to the team level by averaging the responses into a team-level measure of performance.

Team communication

Our measure of team communication balances the IRI organization’s requirement that we minimize the length of the survey with our desire to thoroughly capture the multidimensionality of team communication (Daft & Lengel, 1984). The survey included items measuring four essential aspects of team communication: (a) the nature and extent of team communication (Markulis, Jassawalla, & Sashittal, 2006); (b) team member voice (Carson, Tesluk, & Marrone, 2007); (c) expertise coordination (Faraj & Sproull, 2000); and (d) collaborative interactions, that is, the extent to which members educate and encourage each other to accomplish tasks and promote each other’s success (Jassawalla & Sashittal, 2002). We assessed team communication by asking participants to rate their agreement with eight statements (e.g., “Team members routinely interact with each other and with others outside of the team”; “This team does a great job of communicating and coordinating among members”). Despite the multidimensionality of the scale, principal components factor analysis of the eight items revealed that they loaded onto one factor. We, therefore, averaged the items into a single scale of team communication (Cronbach’s α = .85). We used an interrater reliability coefficient (James, Demaree, & Wolf, 1993) to examine the intragroup reliability (r_WG) of responses. Some scholars have suggested that an r_WG greater or equal to .70 is an indicator of an acceptable level of agreement within a group (George & Bettenhausen, 1990). The average intragroup reliability for this scale for the teams in our sample was .84, supporting the aggregation of individual team member scores into a team-level communication scale.

Geographic dispersion

We followed established practices to measure the degree of geographic dispersion among members of a team (e.g., Gibson & Gibbs, 2006; Gilson et al., 2015; Martins et al., 2004). We calculated our measure at the team level using the Blau Index (Blau, 1977), an index commonly used to measure variability. We performed our evaluation of the variability of team member addresses using the following formula in which p is the proportion of individuals at a location and i is the number of locations:

D = 1 - \sum_{i = 1}^{N} p_{i}^{2} .

We evaluated team dispersion from the perspective of whether there was a difference in address. A value of zero represents a completely collocated team, with no dispersed members, and a value of 1 represents complete geographic dispersion with every member located at a different address.

Transformational leadership

We measured transformational leadership by asking team members to evaluate their leaders’ behaviors along four dimensions associated with transformational leadership (Bass & Avolio, 1994; Pearce & Sims, 2002): providing idealized influence (enthusiastic approach), inspirational motivation (dedication to higher purposes or ideals), individualized consideration (individualized performance expectations), and intellectual stimulation (challenge the status quo). At the individual level, these four dimensions loaded onto a single factor and we averaged them into a scale of transformational leadership (Cronbach’s α = .76). We used an interrater reliability coefficient (James et al., 1993) to examine the intragroup reliability (r_WG) of responses. The average intragroup reliability for this scale for the teams in our sample was .85, indicating an acceptable level of agreement within the groups (George & Bettenhausen, 1990) and supporting the aggregation of individual team member scores into a team-level measure of transformational leadership.

Control variables

We controlled for team size because team size may influence team processes and outcomes (Hülsheger, Anderson, & Salgado, 2009). We also controlled for team tenure (i.e., the average time team members spent on the team), to account for positive performance outcomes associated with the amount of time team members worked together (Hackman, 2002). We assessed team tenure by inquiring about the approximate length of time the members had been on the team using the following response choices: 1 = less than 3 months, 2 = 3 to 6 months, 3 = 6 to 12 months, 4 = 1 to 2 years, 5 = 2 to 4 years, 6 = over 4 years. We averaged the responses across team members for each team, combining them into the team tenure measure. We controlled for diversity in cultural background so that we could isolate the effects of geographic distance from the effects of social distance because previous research has found that cultural differences may influence communication behavior (Han & Beyerlein, 2016; Jarvenpaa & Leidner, 1999; Tsui & Nifadkar, 2007) and may be particularly important in examining team processes in geographically dispersed teams (Staples & Zhao, 2006). We asked survey participants to specify to which national culture they belong. Using their selection, we calculated cultural background diversity at the team level using the Blau Index (Blau, 1977). This approach allowed us to calculate the degree of cultural diversity by evaluating the variability of team member background using the same formula as the one for evaluating geographic dispersion variability. A value of zero represents a team with every member belonging to the same culture, while a value of 1 represents complete diversity with every member of the team belonging to a different culture.

Results

Table 1 provides the means, standard deviations (SDs), and correlations for the variables in our study. On average, team members had been with their respective teams between 1 and 2 years and the average team size was just less than 11 members (SD = 6.54). The average geographic dispersion and its SD indicate a large variation in how dispersed the team members were across teams in our sample. The pattern of correlations among the variables of interest in this study is mostly consistent with our hypothesized relationships. Team communication is significantly correlated with team performance rated by stakeholders (r = .38, p = .006) and team members (r = .83, p < .01). Team dispersion is not significantly correlated with team performance, suggesting that there is considerable variation in those relationships across the teams in our sample. Transformational leadership was correlated with team performance as rated by team members (r = .34, p = .013) but not team performance as rated by stakeholders. For self-reported items, we performed multicollinearity checks, which did not reveal any significant issues. We centered all continuous independent variables to address potential issues related to risks of bias in the size of the coefficient due to multicollinearity (Cohen, Cohen, West, & Aiken, 2003; Marquardt, 1980).

Table 1.

Means, Standard Deviations, and Bivariate Correlations (n = 53).

	M	SD	1	2	3	4	5	6	7	8
1. Team performance (team member evaluation)	5.10	0.62	1	.35*	.16	−.01	.01	.34*	.09	.83**
2. Team performance (stakeholder evaluation)	4.92	1.16	.35*	1.00	−.10	.17	.20	.07	.11	.37**
3. Team tenure	3.71	0.76	.16	−.10	1.00	.12	.06	.42**	.19	.08
4. Team size	10.92	6.54	−.01	.17	.12	1.00	.08	.06	−.01	−.07
5. Cultural diversity	0.34	0.21	.01	.20	.06	.08	1.00	.06	.32*	.00
6. Transformational leadership	5.72	0.47	.34*	.07	.42**	.06	.06	1.00	−.07	.35*
7. Geographic dispersion	0.37	0.26	.09	.11	.19	−.01	.32*	−.07	1.00	.13
8. Team communication	5.39	0.43	.83**	.37**	.08	−.07	.00	.35*	.13	1.00

†

p ≤ .1. *p ≤ .05. **p ≤ .01. ***p ≤ .001.

To test our hypotheses, we performed multivariate ordinary least squares regression. Each model controlled for team tenure, team size, and cultural diversity, which existing research has demonstrated influence variability in team performance. Given our relatively small sample, we treated results equal to (based on rounding) or less than 0.05 level as significant, because we felt that while marginally significant at this level, our results highlighted a pattern that was noteworthy. The results of the analysis of team performance are presented in Tables 2 and 3. Table 2 presents team performance as evaluated by stakeholders and Table 3 presents team performance as evaluated by team members themselves.

Table 2.

Regression Model for Team Performance—Evaluated by Stakeholders (n = 53).

Variables	Model 1	Model 2	Model 3	Model 4
Team tenure	−0.32	−0.51*	−0.34	−0.25
Team size	0.03	0.04	0.04	0.04
Cultural variety	0.80	0.77	0.94	1.04
Transformational leadership	0.37	0.62	0.13
Geographic dispersion	0.52	0.29	0.10
Transformational Leadership × Geographic Dispersion		−2.69*	−1.16
Team communication			0.89*	1.06**
Constant	4.68	4.59
Adjusted R²	.01	.07	.13	.17
∆R²		.06*	.06*	.04*

Note. All coefficients are unstandardized regression coefficients.

†

p ≤ .10. *p ≤ .05. **p ≤ .01. ***p ≤ .001; two tailed.

Table 3.

Regression Model for Team Performance—Evaluated by Team Members (n = 53).

Variables	Model 1	Model 2	Model 3	Model 4
Team tenure	−0.01	−0.19	0.01	0.07
Team size	0.00	0.01	0.01	0.00
Cultural variety	−0.10	−0.15	0.07	0.06
Transformational leadership	0.48*	0.72***	0.12
Geographic dispersion	0.29	0.08	−0.15
Transformational Leadership × Geographic Dispersion		−2.59***	−0.78
Team communication			1.05***	1.16***
Constant	5.13	4.74
Adjusted R²	.04	.30	.67	.67
∆R²		.26***	.37***	.00

Note. All coefficients are unstandardized regression coefficients.

†

p ≤ .10. *p ≤ .05. **p ≤ .01. ***p ≤ .001; two tailed.

In an effort to be parsimonious, as the pattern of results is similar for stakeholder and team member evaluation of team performance, we will base our discussion on the stakeholder evaluations. As expected, team member self-evaluations, while overall similar to stakeholders, were more positive. Model 1 (see Table 2) includes controls and main effects of transformational leadership and geographic team dispersion on team performance as rated by stakeholders. Hypothesis 1 predicted that transformational leadership would negatively moderate the relationship between team dispersion and team performance. To test this hypothesis, we included the team dispersion-transformational leadership interaction term in the models of team performance. We found support for Hypothesis 1. As shown in Model 2 (see Table 2), adding the interaction term yielded a statistically significant change in R² for performance (R² change = .06, p ≤ .05). In addition, we found that transformational leadership was a significant negative moderator of the team dispersion–team performance relationship. Specifically, among teams with greater dispersion, stakeholders and members rated those led by leaders using more of a transformational style of leadership as performing less well than those led by leader using less of a transformational style of leadership (b = −2.69, p ≤ .05). To further examine transformational leadership as a moderator, we evaluated the simple slopes for the relationship between team dispersion and team performance at high and low values of transformational leadership (1 SD above and below the mean). A simple slope analysis revealed that the dispersion slope is marginally statistically significant. Because our sample is relatively small, we interpret results with a p value less than or equal to .05 as statistically significant. Specifically, when transformational leadership is high (b = −16.4, p = .054) and when it is low (b = −13.8, p = .055), the analysis suggests that despite marginal statistical significance, transformational leadership’s effectiveness is questionable across all types of teams. Panels A and B of Figure 2 depicts the nature of the interaction for stakeholder-rated and team member-rated performance, respectively.

Figure 2.

Geographic dispersion and transformational leadership interaction—Panel A: Stakeholder-rated team performance. Panel B: Member-rated team performance.

Hypothesis 2 predicted that transformational leadership would negatively moderate the relationship between team dispersion and team communication. To test this hypothesis, we first evaluated a model of team communication that included only controls and main effects and a second model of team communication that included the team dispersion–transformational leadership interaction term. We found support for Hypothesis 2. We found that the interaction between geographic dispersion and transformational leadership was statistically significant in predicting team communication. The results of the analysis of team communication are presented in Table 4. The main effect is shown in Table 4, Model 1. We added the interaction term to the control and main effect, which yielded a statistically significant change in R² and an overall adjusted R² of .31 (p ≤ .01), as shown in Model 2 (see Table 4). Specifically, the highly dispersed teams reported communicating less well when led by leaders using more of a transformational style of leadership than when led by leaders using less of a transformational style of leadership (b = −1.72, p ≤ .001).

Table 4.

Regression Model for Team Communication (n = 53).

Variables	Team communication
Variables	Model 1	Model 2
Team tenure	−0.07	−0.19*
Team size	0.00	0.00
Cultural variety	−0.18	−0.20
Transformational leadership	0.40**	0.55***
Geographic dispersion	0.36	0.21
Transformational Leadership × Geographic Dispersion		−1.72***
Constant	5.43	5.38
Adjusted R²	.08	.31
∆R²		.22***

Note. All coefficients are unstandardized regression coefficients.

†

p ≤ .10. *p ≤ .05. **p ≤ .01. ***p ≤ .001; two tailed.

To further examine transformational leadership as a moderator, we assessed the simple slopes for the relationship between team dispersion and team communication at high and low values of transformational leadership (1 SD above and below the mean). A simple slope analysis revealed that the dispersion slope is negative and statistically significant both when transformational leadership is high (b = −10.5, p = .000) and when it is low (b = −8.89, p = .000). Figure 3 depicts the nature of the interaction.

Figure 3.

Team communication: Geographic dispersion and transformational leadership interaction.

Hypothesis 3 predicted that communication would mediate the moderating effect of transformational leadership on the team dispersion-team performance relationship. We tested the mediated moderation model using the procedures recommended to integrate moderation and mediation for such analysis (Baron & Kenny, 1986) and found support for Hypothesis 3. Our approach, which is consistent with the three steps delineated by Baron and Kenny (1986), demonstrates mediation. Step 1 is shown in Model 2 (see Table 2). It illustrates the moderating influence of transformational leadership on the relationship between geographic distribution and team performance. Step 2 is depicted in Model 2 (see Table 4). It demonstrates that transformational leadership moderates the relationship between team dispersion and team communication (b = −1.72, p ≤ .001). Step 3 is depicted in Model 4 (see Table 2). It shows that team communication significantly accounts for the variability in team performance (b = 1.06, p ≤ .01). As shown in Table 2, the coefficient for the team dispersion–transformational leadership interaction loses statistical significance when team communication is added to the model, with team communication taking over the effect on performance (b = 0.89, p ≤ .05). Thus, the moderating effect of transformational leadership on the team dispersion–team performance relationship is mediated by team communication, supporting Hypothesis 3.

Discussion

This study contributes to the literature on team dispersion by offering a nuanced understanding of the relationship between geographic dispersion, team leadership, team communication, and team performance. We clarified the effects of geographic dispersion on team communication and team performance, examined the role of transformational leadership in affecting these relationships, and demonstrated the boundaries to the effectiveness of transformational leadership. Results from our study show that transformational leadership is not always helpful and that highly geographically dispersed teams may need another approach to help them address challenges associated with team member dispersion to reduce the negative effects on team communication and performance. We show that a transformational leader’s influence on both team communication and team performance is less in teams characterized by high levels of dispersion than in teams that are collocated. Specifically, our results reveal that in contrast to collocated teams, in highly geographically dispersed teams, transformational leadership’s influence on team communication progressively decreases as the teams become more and more dispersed. This diminished communication effect helps explain the lower performance of teams characterized by high levels of dispersion. This may be due to the increasing difficulties experienced by team members in communicating with each other and their team leader, as dispersion increases. In teams characterized by greater dispersion, team members are operating across a variety of contexts and norms that may be specific to their location, which may make it difficult for members to understand each other and create increased difficulties in their interactions and relationships. In highly dispersed teams, even a transformational leader may be “too far removed” to be perceived as someone who is authentic and who genuinely wants to make a difference. In dispersed teams, transformational leadership is less helpful than it seems to be for collocated teams.

We question how leadership has been thought of over the last few decades by examining it in the context of geographically dispersed teams, where team members collaborate using technology that may or may not replace key human interactions. Our study results provide evidence of limitations in the effectiveness of transformational leadership. Specifically, our study suggests that as transformational leadership is not as effective in dispersed teams than in collocated teams, this is an area that should be further examined by future studies. By juxtaposing our results with those of experimental studies, we illuminate below possible avenues for further research on the dispersion–performance relationship. In an experimental study that compared face-to-face teams with teams that relied only on computer-mediated communication, Purvanova and Bono (2009) found transformational leadership to be an effective predictor of performance of the dispersed student teams, even more so than of those teams collaborating only face to face, when working on business project proposals judged for comprehensiveness and creativity, among other factors. While that study compared only the two extremes of dispersion, our study shows how, on a continuum of dispersion, transformational leadership becomes less effective as the team environment becomes more geographically dispersed. This suggests that the moderating effect of leadership may be interconnected with certain configurations of geographic dispersion (Gibson & Gibbs, 2006).

Furthermore, our study is different from that of Purvanova and Bono (2009), in that, in contrast to the small student teams doing role-playing in their experimental setting, we rely on industry teams with real-world outcomes at stake. Our findings suggest that team tenure, team size, and leader experience may help explain why transformational leaders’ efforts at leveraging team dispersion for high performance yields inconsistent results, highlighting another area for future studies. Scholars may want to study further how geographic dispersion influences the effectiveness of transformational leadership across different communication media.

The results from our study further inform the literature on geographically dispersed teams by identifying the limitations of the extent to which transformational leadership can facilitate team communication and performance in highly dispersed teams. Earlier studies have suggested the boundaries to the effectiveness of transformational leadership (e.g., Wofford, Whittington, & Goodwin, 2001). We show that transformational leadership mitigates not just the dispersion–performance relationship but also the dispersion–communication relationship. Whether transformational leadership combined with increased team dispersion also mitigates the emergence of other team dynamics and states, such as trust, cohesion, and team identity (Kirkman, Rosen, Gibson, Tesluk, & PcPherson, 2002), is a question for further empirical and theoretical study. Finally, our findings are noteworthy because, in our study, we intentionally isolated the effect of spatial distance among members (i.e., team dispersion) from that of social distance (i.e., cultural diversity). Future studies may want to examine the differences in the effects of various types of distance.

Geographically dispersed teams tend to perform better when team members self-regulate performance patterns as compared with when leaders unilaterally direct teams (Kozlowski, Gully, McHugh, Salas, & Cannon-Bowers, 1996). Transformational team leaders should, therefore, not only consider being proactive and provide structure and a clear direction but also develop ways to enable team members themselves to be more involved in regulating team processes and performance.

Practical implications from our study highlight the importance of not taking a one-size-fits-all approach and relying on transformational leadership in all situations. Although many accept transformational leadership as a prominent approach to leading a team, even as the de facto model for successful team performance, we show it is not helpful in all situations. Perhaps transformational leadership could be combined with other approaches to management that would facilitate increased team communication and that would work better in highly dispersed settings. For example, earlier research suggested that shifting some leadership responsibilities to team members in a geographically dispersed context may have a positive impact on team functioning and performance (Carte, Chidambaram, & Becker, 2006; Hoch & Kozlowski, 2014; Liao, 2017). Therefore, rather than focusing attention on transformational leadership itself, it may be worthwhile to shift more attention to fostering leadership among team members of geographically dispersed teams. Organizations may want to devote resources to providing additional training as well as incentives to facilitate greater emergence of leaders in dispersed teams as well as recognize leaders who create opportunities for their dispersed followers to step up. Furthermore, increasing the focus on improving team communication may help geographically distributed teams work better together.

Limitations and Future Research Directions

Although our study had multiple limitations, we believe our findings lay the groundwork for multiple future studies, which we highlight in this section. One limitation of our study is that our participating organizations, as is the case with many field studies, placed a limit on the survey length, which had the effect of restricting the number of items we could include in the survey. Therefore, our measure of communication, for example, while including items measuring multiple dimensions of communication, cannot be separated into distinct communication dimensions. We were also limited in analyzing in-depth interactions among team members and had to rely on their recollected perceptions of team communication. Future studies using network analysis may be particularly effective at uncovering the detailed underlying mechanisms of geographically dispersed team member communication patterns, including the role of the leader in facilitating team member communications and perhaps contrasting the effects of different leadership approaches. Given the positive effects that have been found with increased shared leadership in geographically dispersed teams, future research may want to study the effects on team performance when team members have more opportunities to engage in leadership behaviors. A related topic for all teams may be how hierarchy works between leaders and followers. Another limitation, which is typical in studies of teams in organizations, is that we did not compile longitudinal data. Our decision to collect data at one point in time was a sensible one given that teams may rapidly change in composition and that managers sponsoring the research are also increasingly mobile. Nevertheless, whether temporal trends play a role in how geographic distance affects communication, team dynamics, and, in turn, performance is an empirical question that merits further research and may be best examined in a longitudinal study. A potential limitation of our study is that, by using the same source data (i.e., team members) for the measures of team communication and transformational leadership, we ran the risk of multicollinearity bias. However, we mitigated this risk by having individuals from outside of the team (i.e., the stakeholders) provide performance data as well (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Future studies may want to examine the reciprocal nature of relationships among geographically dispersed team members.

Our study was focused only on transformational leadership. Future studies may want to contrast the results for transformational leadership with other leadership styles to get a more nuanced perspective on which styles of leadership may be especially well suited for fostering team communication and performance in teams with geographically dispersed members working on complex tasks such as innovation.

Conclusion

As geographically dispersed teams continue to gain in popularity, understanding how team dispersion influences team performance will become increasingly important, not just to scholars but also to practicing managers. Although it may be very helpful in some environments, transformational leadership may be limited in its influence on geographically dispersed teams. Therefore, it will be important to continue exploration of factors that help mitigate the challenges associated with highly dispersed teams. Our study demonstrates that to leverage fully the potential benefits of highly geographically dispersed teams, managers who have embraced transformational leadership may need to monitor carefully how their leadership style enhances team communication among dispersed team members because in this context, effective communication is a critical determinant of team performance.

Footnotes

Acknowledgements

The authors would like to thank Theresa Lant and anonymous reviewers for their detailed and constructive comments on earlier versions of this article.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Science Foundation (NSF) under Award No. SES-0852671. The authors also recognize the support of the Industrial Research Institute (IRI) in providing access to member companies for the purpose of this study. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the NSF or the IRI.

Author Biographies

Julia Eisenberg (PhD, Rutgers University) is assistant professor of management at Pace University’s Lubin School of Business, USA. Prior to academia, she spent a decade working in the financial industry. Her research interests include collaboration among geographically distributed individuals and teams, leadership, and identification processes.

Corinne Post (PhD, Rutgers University) is a professor of management at Lehigh University’s College of Business & Economics, USA. Her research interests comprise gender and leadership (including in upper echelons); mechanisms underlying gender, racial, or ethnic differences in careers; and diversity as enabler or impediment to group and organizational performance.

Nancy DiTomaso (PhD, University of Wisconsin–Madison) is distinguished professor in the Department of Management and Global Business at Rutgers Business School–Newark and New Brunswick, USA. Her research interests include diversity, culture, and inequality.

References

Ahuja

M. K.

Galvin

J. E.

(2003). Socialization in virtual groups. Journal of Management, 29, 161-185. doi:10.1016/S0149-2063(02)00213-1

Ancona

D. G.

Caldwell

D. F.

(1992). Demography and design: Predictors of new product team performance. Organization Science, 3, 321-341. doi:10.1287/orsc.3.3.321

Andres

H. P.

(2002). A comparison of face-to-face and virtual software development teams. Team Performance Management, 1, 39-48. doi:10.1108/13527590210425077

Avolio

B. J.

Bass

B. M.

(2001). Developing potential across a full range of Leadership TM: Cases on transactional and transformational leadership. New York, NY: Psychology Press.

Avolio

Walumbwa

F. O.

Weber

T. J.

(2009). Leadership: Current theories, research, and future directions. Annual Review of Psychology, 60, 421-449. doi:10.1146/annurev.psych.60.110707.163621

Balthazard

P. A.

Waldman

D. A.

Warren

J. E.

(2009). Predictors of the emergence of transformational leadership in virtual decision teams. Leadership Quarterly, 651-663. doi:10.1016/j.leaqua.2009.06.008

Baron

R. M.

Kenny

D. A.

(1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182.

Bass

B. M.

(1985). Leadership and performance beyond expectations. New York, NY: Free Press.

Bass

B. M.

Avolio

(1994). Improving organizational effectiveness through transformational leadership. Thousand Oaks, CA: SAGE.

10.

Bass

B. M.

Riggio

R. E.

(2006). Transformational leadership (2nd ed.). London, England: Taylor & Francis.

11.

Bass

B. M.

Steidlmeier

(1999). Ethics, character, and authentic transformational leadership behavior. The Leadership Quarterly, 10, 181-217. doi:10.1016/S1048-9843(99)00016-8

12.

Bell

B. S.

Kozlowski

S. W. J.

(2002). A typology of virtual teams: Implications for effective leadership. Group & Organization Management, 27, 14-49. doi:10.1177/1059601102027001003

13.

Blau

P. M.

(1977). Inequality and heterogeneity. New York, NY: Free Press.

14.

Boerner

Eisenbeiss

S. E.

Griesser

(2007). Follower behavior and organizational performance: The impact of transformational leaders. Journal of Leadership & Organizational Studies, 13, 15-26. doi:10.1177/10717919070130030201

15.

Boutellier

Gassman

Macho

Roux

(1998). Management of dispersed product development teams: The role of information technologies. R&D Management, 28, 13-25.

16.

Braun

Peus

Weisweiler

Frey

(2013). Transformational leadership, job satisfaction, and team performance: A multilevel mediation model of trust. The Leadership Quarterly, 24, 270-283. doi:10.1016/j.leaqua.2012.11.006

17.

Carson

J. B.

Tesluk

P. E.

Marrone

J. A.

(2007). Shared leadership in teams: An investigation of antecedent conditions and performance. Academy of Management Journal, 50, 1217-1234.

18.

Carte

T. A.

Chidambaram

Becker

(2006). Emergent leadership in self-managed virtual teams. Group Decision and Negotiation, 15, 323-343. doi:10.1007/s10726-006-9045-7

19.

Charlier

S. D.

Stewart

G. L.

Greco

L. M.

Reeves

C. J.

(2016). Emergent leadership in virtual teams: A multilevel investigation of individual communication and team dispersion antecedents. Leadership Quarterly, 27, 745-754. doi:10.1016/j.leaqua.2016.05.002

20.

Chidambaram

Jones

(1993). Impact of communication medium and computer support on group perceptions and performance: A comparison of face-to-face and dispersed meetings. MIS Quarterly, 17, 465-491.

21.

Cohen

West

S. G.

Aiken

L. S.

(2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum.

22.

Cordery

J. L.

Soo

(2008). Overcoming impediments to virtual team effectiveness. Human Factors, 18, 487-500. doi:10.1002/hfm.20119

23.

Cramton

(2001). The mutual knowledge problem and its consequences for dispersed collaboration. Organization Science, 12, 346-371. doi:10.1287/orsc.12.3.346.10098

24.

Daft

R. L.

Lengel

(1984). Information richness: A new approach to manager information processing and organizational design. In Staw

B. M.

Cummings

(Eds.), Research in organizational behavior (pp. 191-233). Greenwich, CT: JAI Press.

25.

Dennis

A. R.

Fuller

R. M.

Valacich

J. S.

(2008). Media, tasks, and communication processes: A theory of media synchronicity. MIS Quarterly, 32, 575-600. doi:10.2307/25148857

26.

Dionne

Yammarino

Atwater

Spangler

(2004). Transformational leadership and team performance. Journal of Organizational Change Management, 17, 177-193. doi:10.1108/09534810410530601

27.

Dulebohn

J. H.

Hoch

J. E.

(2017). Virtual teams in organizations. Human Resource Management Review, 27, 569-694. doi:10.1007/s10787-012-0152-6

28.

Dvir

Eden

Avolio

Shamir

(2002). Impact of transformational leadership on follower development and performance: A field experiment. Academy of Management Journal, 45, 735-744. doi:10.5465/3069307

29.

Ebrahim

Ahmed

Taha

(2009). Innovation and R&D activities in virtual team. European Journal of Scientific Research, 34, 297-307.

30.

Edmondson

(1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44, 350. doi:10.2307/2666999

31.

Faraj

Sproull

(2000). Coordinating expertise in software development teams. Management Science, 46, 1554-1568.

32.

Ferreira

P. G. S.

de Lima

E. P.

da Costa

S. E. G.

(2012). Perception of virtual team’s performance: A multinational exercise. International Journal of Production Economics, 140, 416-430. doi:10.1016/j.ijpe.2012.06.025

33.

Foster

M. K.

Abbey

Callow

M. A.

Wilbon

A. D.

(2015). Rethinking virtuality and its impact on teams. Small Group Research, 46, 267-299. doi:10.1177/1046496415573795

34.

George

J. M.

Bettenhausen

(1990). Understanding prosaic behavior, sales performance, and turnover: A group-level analysis in a service context. Journal of Applied Psychology, 75, 698-709. doi:10.1037/0021-9010.75.6.698

35.

Gibbs

Rozaidi

N. A.

Eisenberg

(2013). Overcoming the “ideology of openness”: Probing the affordances of social media for organizational knowledge sharing. Journal of Computer-Mediated Communication, 19, 102-120. doi:10.1111/jcc4.12034

36.

Gibson

C. B.

Gibbs

J. L.

(2006). Unpacking the concept of virtuality: The effects of geographic dispersion, electronic dependence, dynamic structure, and national diversity on team innovation. Administrative Science Quarterly, 51, 451-495. doi:10.2189/asqu.51.3.451

37.

Gilson

Maynard

M. T.

Jones Young

N. C.

Vartiainen

Hakonen

(2015). Virtual teams research: 10 years, 10 themes, and 10 opportunities. Journal of Management, 41, 1313-1337. doi:10.1177/0149206314559946

38.

Grant

A. M.

Hofmann

D. A.

(2011). Outsourcing inspiration: The performance effects of ideological messages from leaders and beneficiaries. Organizational Behavior and Human Decision Processes, 116, 173-187. doi:10.1016/j.obhdp.2011.06.005

39.

Hackman

J. R.

(2002). Leading teams: Setting the stage for great performances. Boston, MA: Harvard Business School Press.

40.

Hambley

Kline

(2007). Virtual team leadership: Perspectives from the field. International Journal of E-Collaboration, 3, 40-64. doi:10.4018/jec.2007010103

41.

Hambley

O’Neill

Kline

(2007). Virtual team leadership: The effects of leadership style and communication medium on team interaction styles and outcomes. Organizational Behavior and Human Decision Processes, 103, 1-20. doi:10.1016/j.obhdp.2006.09.004

42.

Han

S. J.

Beyerlein

(2016). Framing the effects of multinational cultural diversity on virtual team processes. Small Group Research, 47, 351-383. doi:10.1177/1046496416653480

43.

Hardin

A. M.

Fuller

M. A.

Davison

R. M.

(2007). I know I can, but can we? Culture and efficacy beliefs in global virtual teams. Small Group Research, 38, 130-155. doi:10.1177/1046496406297041

44.

Hertel

Geister

Konradt

(2005). Managing virtual teams: A review of current empirical research. Human Resource Management Review, 15, 69-95. doi:10.1016/j.hrmr.2005.01.002

45.

Hinds

Bailey

D. E.

(2003). Out of sight, out of sync: Understanding conflict in distributed teams. Organization Science, 14, 615-632. doi:10.1287/orsc.14.6.615.24872

46.

Hinds

Mortensen

(2005). Understanding conflict in geographically teams: The moderating effects of shared identity, shared context, and spontaneous communication. Organization Science, 16, 290-307. doi:10.1287/orsc.1050.0122

47.

Hoch

J. E.

Kozlowski

S. W. J.

(2014). Leading virtual teams: Hierarchical leadership, structural supports, and shared team leadership. Journal of Applied Psychology, 99, 390-403. doi:10.1037/a0030264

48.

House

Spangler

Woycke

(1991). Personality and charisma in the U.S. presidency: A psychological theory of leader effectiveness. Administrative Science Quarterly, 36, 364-396. doi:10.2307/2393201

49.

Howell

J. M.

Hall-Merenda

K. E.

(1999). The ties that bind: The impact of leader-member exchange, transformational and transactional leadership, and distance on predicting follower performance. Journal of Applied Psychology, 84, 680-694. doi:10.1037//0021-9010.84.5.680

50.

Howell

J. M.

Neufeld

D. J.

Avolio

(2005). Examining the relationship of leadership and physical distance with business unit performance. The Leadership Quarterly, 16, 273-285. doi:10.1016/j.leaqua.2005.01.004

51.

Hoyt

C. L.

Blascovich

(2003). Transformational and transactional leadership in virtual and physical environments. Small Group Research, 34, 678-715. doi:10.1177/1046496403257527

52.

Hülsheger

U. R.

Anderson

Salgado

J. F.

(2009). Team-level predictors of innovation at work: A comprehensive meta-analysis. Journal of Applied Psychology, 94, 1128-1145. doi:10.1037/a0015978

53.

James

L. R.

Demaree

R. G.

Wolf

(1993). Rwg: An assessment of within-group interrater agreement. Journal of Applied Psychology, 78, 306-309. doi:10.1037/0021-9010.78.2.306

54.

Jarvenpaa

Leidner

D. E.

(1999). Communication and trust in global virtual teams. Organization Science, 10, 791-815. doi:10.1287/orsc.10.6.791

55.

Jassawalla

Sashittal

(2002). Cultures that support product-innovation processes. Academy of Management Executive, 16, 42-54. doi:10.5465/AME.2002.8540307

56.

Kayworth

T. R.

Leidner

D. E.

(2002). Leadership effectiveness in global virtual teams. Journal of Management Information Systems, 18, 7-40. doi:10.1080/07421222.2002.11045697

57.

Kirkman

B. L.

Mathieu

J. E.

(2005). The dimensions and antecedents of team virtuality. Journal of Management, 31, 700-718. doi:10.1177/0149206305279113

58.

Kirkman

B. L.

Rosen

Gibson

Tesluk

PcPherson

(2002). Five challenges to virtual team success: Lessons from Sabre, Inc. Academy of Management Executive, 16, 67-79.

59.

Kozlowski

S. W. J.

Gully

S. M.

McHugh

P. P.

Salas

Cannon-Bowers

J. A.

(1996). A dynamic theory of leadership and team effectiveness: Developmental and task contingent leader roles. In Ferris

(Ed.), Research in personnel and human resource management (pp. 253-305). Greenwich, CT: JAI Press.

60.

Kratzer

Leenders

R. T. A. J.

Van Engelen

J. M. L.

(2006). Managing creative team performance in virtual environments: An empirical study in 44 R&D teams. Technovation, 26, 42-49. doi:10.1016/j.technovation.2004.07.016

61.

Latham

G. P.

Ernst

(2006). Keys to motivating tomorrow’s workforce. Human Resource Management Review, 16, 181-198. doi:10.1016/j.hrmr.2006.03.014

62.

Leenders

R. T. A.

van Engelen

J. M.

Kratzer

(2003). Virtuality, communication, and new product team creativity: A social network perspective. Journal of Engineering and Technology Management, 20, 69-92. doi:10.1016/S0923-4748(03)00005-5

63.

Mitchell

Boyle

(2016). The divergent effects of transformational leadership on individual and team innovation. Group & Organization Management, 41, 66-97. doi:10.1177/1059601115573792

64.

Liao

(2017). Leadership in virtual teams: A multilevel perspective. Human Resource Management Review, 27, 648-659. doi:10.1007/s10787-012-0152-6

65.

Lin

S.-H.

Scott

B. A.

Matta

(2018). The dark side of transformational leader behaviors for leaders themselves: A conservation of resources perspective. Academy of Management Journal. Advance online publication. doi:10.2224/sbp.2009.37.8.1017

66.

Lindell

Whitney

D. J.

(2001). Accounting for common method variance in cross-sectional research designs. Journal of Applied Psychology, 86, 114-121. doi:10.1037//0021-9010.86.1.114

67.

Lipnack

Stamps

(1997). Virtual teams. New York, NY: John Wiley.

68.

Lowe

K. B.

Kroeck

K. G.

Sivasubramaniam

(1996). Effectiveness correlates of transformational and transactional leadership: A meta-analytic review of the MLQ literature. Leadership Quarterly, 7, 385-425. doi:10.1016/S1048-9843(96)90027-2

69.

Markulis

Jassawalla

A. R.

Sashittal

(2006). The impact of leadership modes on team dynamics and performance in undergraduate management classes. Journal of Education for Business, 33, 247-252.

70.

Marlow

S. L.

Lacerenza

C. N.

Salas

(2017). Communication in virtual teams: A conceptual framework and research agenda. Human Resource Management Review, 27, 575-589. doi:10.1016/j.hrmr.2016.12.005

71.

Marquardt

D. W.

(1980). You should standardize the predictor variables in your regression models. Journal of the American Statistical Association, 75, 87-91. doi:10.1080/01621459.1980.10477430

72.

Martins

Gilson

Maynard

M. T.

(2004). Virtual teams: What do we know and where do we go from here? Journal of Management, 30, 805-835. doi:10.1016/j.jm.2004.05.002

73.

Mathieu

J. E.

Maynard

M. T.

Rapp

T. L.

Gilson

(2008). Team effectiveness 1997-2007: A review of recent advancements and a glimpse into the future. Journal of Management, 34, 410-476. doi:10.1177/0149206308316061

74.

May

Carter

(2001). A case study of virtual team working in the European automotive industry. International Journal of Industrial Ergonomics, 27, 171-186. doi:10.1016/S0169-8141(00)00048-2

75.

Maynard

M. T.

Mathieu

J. E.

Rapp

T. L.

Gilson

(2012). Something(s) old and something(s) new: Modeling drivers of global virtual team effectiveness. Journal of Organizational Behavior, 365, 342-365. doi:10.1002/job

76.

McLeod

P. L.

(2013). Distributed people and distributed information: Vigilant decision-making in virtual teams. Small Group Research, 44, 627-657. doi:10.1177/1046496413500696

77.

Ortiz

Guinea

Webster

Staples

D. S.

(2012). A meta-analysis of the consequences of virtualness on team functioning. Information & Management, 49, 301-308. doi:10.1016/j.im.2012.08.003

78.

Pawar

Eastman

K. K.

(1997). The nature and implications contextual influences on transformational leadership: A conceptual examination. Academy of Management Review, 22, 80-109. doi:10.2307/259225

79.

Pearce

C. L.

Sims

H. P.

(2002). Vertical versus shared leadership as predictors of the effectiveness of change management teams: An examination of aversive, directive, transactional, transformational, and empowering leader behaviors. Group Dynamics: Theory, Research, and Practice, 6, 172-197. doi:10.1037//1089-2699.6.2.172

80.

Perry

S. J.

Lorinkova

N. M.

Hunter

E. M.

Hubbard

Mcmahon

J. T.

(2016). When does virtuality really “work”? Examining the role of work–family and virtuality in social loafing. Journal of Management, 42, 449-479. doi:10.1177/0149206313475814

81.

Podsakoff

O. P.

MacKenzie

Lee

Podsakoff

(2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88, 879-903. doi:10.1037/0021-9010.88.5.879

82.

Podsakoff

O. P.

MacKenzie

Moorman

Fetter

(1990). Transformational leader behaviors and their effects of followers’ trust in leader, satisfaction and organizational citizenship behaviors. The Leadership Quarterly, 1, 107-142. doi:10.1016/1048-9843(90)90009-7

83.

Powell

Piccoli

Ives

(2004). Virtual teams: A review of current literature and directions for future research. ACM SIGMIS Database, 35, 6-36. doi:10.1145/968464.968467

84.

Price

T. L.

(2003). The ethics of authentic transformational leadership. The Leadership Quarterly, 14, 67-81. doi:10.1016/S1048-9843(02)00187-X

85.

Purvanova

Bono

(2009). Transformational leadership in context: Face-to-face and virtual teams. The Leadership Quarterly, 20, 343-357. doi:10.1016/j.leaqua.2009.03.004

86.

Rafferty

A. E.

Griffin

M. A.

(2004). Dimensions of transformational leadership: Conceptual and empirical extensions. The Leadership Quarterly, 15, 329-354. doi:10.1016/j.leaqua.2004.02.009

87.

Reed

Knight

(2010). Effect of a virtual project team environment on communication-related project risk. International Journal of Project Management, 28, 422-427. doi:10.1016/j.ijproman.2009.08.002

88.

Shamir

House

Arthur

(1993). The motivational effects of charismatic leadership: A self-concept based theory. Organization Science, 4, 577-594. doi:10.1287/orsc.4.4.577

89.

Smith

M. J.

Arthur

Hardy

Callow

Williams

(2013). Transformational leadership and task cohesion in sport: The mediating role of intrateam communication. Psychology of Sport and Exercise, 14, 249-257. doi:10.1016/j.psychsport.2012.10.002

90.

Sosik

Avolio

Kahai

Jung

D. I.

(1998). Computer-supported work group potency and effectiveness: The role of transformational leadership, anonymity, and task interdependence. Computers in Human Behavior, 14, 491-511. doi:10.1016/S0747-5632(98)00019-3

91.

Staples

D. S.

Zhao

(2006). The effects of cultural diversity in virtual teams versus face-to-face teams. Group Decision and Negotiation, 15, 389-406. doi:10.1007/s10726-006-9042-x

92.

Thatcher

S. M. B.

Patel

P. C.

(2011). Group faultlines: A review, integration, and guide to future research. Journal of Management, 38, 969-1009. doi:10.1177/0149206311426187

93.

Tourish

(2013). The dark side of transformational leadership: A critical perspective. London, England: Routledge.

94.

Tsui

A. S.

Nifadkar

S. S.

(2007). Cross-national, cross-cultural organizational behavior research: Advances, gaps, and recommendations. Journal of Management, 33, 426-478. doi:10.1177/0149206307300818

95.

Van den Bulte

Moenaert

R. K

. (1998). The effects of R&D team co-location on communication patterns among R&D, marketing, and manufacturing. Management Science, 44, S1-S18. doi:10.1287/mnsc.44.11.S1

96.

van Knippenberg

Sitkin

S. B

. (2013). A critical assessment of charismatic—Transformational leadership research: Back to the drawing board? Academy of Management Annals, 7, 1-60. doi:10.1080/19416520.2013.759433

97.

Walter

Bruch

(2010). Structural impacts on the occurrence and effectiveness of transformational leadership: An empirical study at the organizational level of analysis. The Leadership Quarterly, 21, 765-782. doi:10.1016/j.leaqua.2010.07.006

98.

Walther

J. B.

(1995). Relational aspects of computer-mediated communication: Experimental observations over time. Organization Science, 6, 186-203. doi:10.1287/orsc.6.2.186

99.

Walther

J. B.

Bunz

(2005). The rules of virtual groups: Trust, liking, and performance in computer mediated communication. Journal of Communication, 55, 828-846. doi:10.1111/j.1460-2466.2005.tb03025.x

100.

Wang

I. S.

Courtright

S. H.

Colbert

A. E.

(2011). Transformational leadership and performance across criteria and levels: A meta-analytic review of 25 years of research. Group & Organization Management, 36, 223-270. doi:10.1177/1059601111401017

101.

Wang

Walther

J. B.

Hancock

J. T.

(2009). Social identification and interpersonal communication in computer-mediated communication: What you do versus who you are in virtual groups. Human Communication Research, 35, 59-85. doi:10.1111/j.1468-2958.2008.01338.x

102.

Warkentin

Beranek

P. M.

(1999). Training to improve virtual team communication. Information Systems Journal, 9, 271-289. doi:10.1046/j.1365-2575.1999.00065.x

103.

Wax

DeChurch

L. A.

Contractor

N. S.

(2017). Self-organizing into winning teams: Understanding the mechanisms that drive successful collaborations. Small Group Research, 48, 665-718. doi:10.1177/1046496417724209

104.

Wofford

J. C.

Whittington

J. L.

Goodwin

V. L.

(2001). Follower motive patterns as situational moderators for transformational leadership effectiveness. Journal of Managerial Issues, 13, 196-211.

105.

Yammarino

(1994). Transformational leadership at a distance. In Bass

B. M.

Avolio

B. J.

(Eds.), Improving organizational effectiveness through transformational leadership (pp. 26-47). Thousand Oaks, CA: SAGE.

106.

Yilmaz

Youngreen

(2016). The application of minority influence theory in computer-mediated communication groups. Small Group Research, 47, 692-719. doi:10.1177/1046496416661033

107.

Zhu

Avolio

Riggio

R. E.

Sosik

J. J.

(2011). The effect of authentic transformational leadership on follower and group ethics. The Leadership Quarterly, 22, 801-817. doi:10.1016/j.leaqua.2011.07.004

108.

Zigurs

(2003). Leadership in virtual teams: Oxymoron or opportunity? Organizational Dynamics, 31, 339-351.