ArticlePDF Available

Leading Virtual Teams: Hierarchical Leadership, Structural Supports, and Shared Team Leadership

December 2012
Journal of Applied Psychology 99(3)

Source
PubMed

Authors:

California State University, Northridge

Using a field sample of 101 virtual teams, this research empirically evaluates the impact of traditional hierarchical leadership, structural supports, and shared team leadership on team performance. Building on Bell and Kozlowski's (2002) work, we expected structural supports and shared team leadership to be more, and hierarchical leadership to be less, strongly related to team performance when teams were more virtual in nature. As predicted, results from moderation analyses indicated that the extent to which teams were more virtual attenuated relations between hierarchical leadership and team performance but strengthened relations for structural supports and team performance. However, shared team leadership was significantly related to team performance regardless of the degree of virtuality. Results are discussed in terms of needed research extensions for understanding leadership processes in virtual teams and practical implications for leading virtual teams. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Content uploaded by Julia E. Hoch

Content may be subject to copyright.

Leading Virtual Teams: Hierarchical Leadership, Structural Supports, and

Shared Team Leadership

Julia E. Hoch and Steve W. J. Kozlowski

Michigan State University

Using a field sample of 101 virtual teams, this research empirically evaluates the impact of traditional

hierarchical leadership, structural supports, and shared team leadership on team performance. Building

on Bell and Kozlowski’s (2002) work, we expected structural supports and shared team leadership to be

more, and hierarchical leadership to be less, strongly related to team performance when teams were more

virtual in nature. As predicted, results from moderation analyses indicated that the extent to which teams

were more virtual attenuated relations between hierarchical leadership and team performance but

strengthened relations for structural supports and team performance. However, shared team leadership

was significantly related to team performance regardless of the degree of virtuality. Results are discussed

in terms of needed research extensions for understanding leadership processes in virtual teams and

practical implications for leading virtual teams.

Keywords: team virtuality, virtual team leadership, structural supports, shared team leadership, team

performance

Virtual teams work together over time and distance via elec-

tronic media to combine effort and achieve common goals (Bell &

Kozlowski, 2002). Although surveys indicate that fewer than 50%

of companies used virtual teams in 2000, by 2008 over 65% stated

that their reliance on virtual teams would “mushroom” in the

future. Moreover, among companies with over 10,000 employees,

the use of virtual teams was projected to be 80% (i4cp, 2006,

2008). Concurrent with this growth in the use of virtual teams, the

literature on virtual teams has been increasing (Cheshin, Rafaeli, &

Bos, 2011;Hill, Bartol, Tesluk, & Langa, 2009;Majchrzak, Mal-

hotra, Stamps, & Lipnack, 2004;Martins & Shalley, 2011;

Mesmer-Magnus, DeChurch, Jimenez-Rodriguez, Wildman, &

Shuffler, 2011;Peters & Karren, 2009;Sarker, Anjuja, Sarker, &

Kirkeby, 2011;Shin, 2004).

Most research has focused on the advantages and disadvan-

tages of virtual teams. Relative to face-to-face teams, benefits

attributed to the use of virtual teams include the ability to

compose a team of experts flung across space and time, in-

creases in staffing flexibility to meet market demands, and cost

savings from reduced travel (Kirkman, Gibson, & Kim, 2012;

Kirkman & Malthieu, 2005;Stanko & Gibson, 2009). Disad-

vantages include lower levels of team cohesion, work satisfac-

tion, trust, cooperative behavior, social control, and commit-

ment to team goals; all factors that can negatively impact team

performance.

In light of these concerns, it is surprising that relatively

limited research attention has been directed toward virtual team

leadership (Gibson & Gibbs, 2006;Kirkman et al., 2012;Mar-

tins, Gilson, & Maynard, 2004;O’Leary & Mortensen, 2010;

Siebdraht, Hoegl, & Ernst, 2009). Team leadership is regarded

as a key mechanism for minimizing motivation and coordina-

tion losses and maintaining team effectiveness when they are

virtual (Bell & Kozlowski, 2002;Malhotra, Majchrzak, &

Rosen, 2007;Martins et al., 2004;Zigurs, 2003). However, one

particular concern is that traditional hierarchical leadership

processes are expected to be disadvantaged in virtual teams

because of the lack of face-to-face contact. Thus, some scholars

have suggested that hierarchical leadership processes may need

to be supplemented in virtual teams as a way to augment team

effectiveness (Avolio, Kahai, & Dodge, 2000;Bell & Kozlow-

ski, 2002). The purpose of this research is to investigate the

impact of team leadership on team performance in teams that

span degrees of virtuality. Although this perspective has been

proposed in the theoretical literature, it has not been examined

empirically. In particular, we examine the extent to which

structural supports and shared team leadership supplement hi-

erarchical leadership and the extent to which these relationships

are moderated by the degree of virtuality.

Editor’s Note. Eduardo Salas served as the action editor for this article.—

S.W.J.K.

This article was published Online First December 3, 2012.

Julia E. Hoch, School of Human Resources and Labor Relations, Mich-

igan State University; Steve W. J. Kozlowski, Department of Psychology,

Michigan State University.

The first author would like to acknowledge the German Research Foun-

dation (Grant No. 1412/6-1, U. Konradt, PI) for funding that, in part,

provided support during her doctoral dissertation research and Dr. Konradt

for serving as Chair of her doctoral thesis committee. Nonetheless, any

opinions, findings, and conclusions or recommendations expressed are

those of the authors and do not necessarily reflect the views of the DFG.

Correspondence concerning this article should be addressed to Julia E.

Hoch, who is now at California State University, Northridge, College of

Business and Economics, Department of Management, Juniper Hall

JH4216, 18111 Nordhoff Street, Northridge, CA 91330, or to Steve W. J.

Kozlowski, Michigan State University, Department of Psychology, 309

Psychology Building, East Lansing, MI 48824. E-mail: julia.hoch@csun

.edu or je.hoch1@gmail.com or stevekoz@msu.edu

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

2014, Vol. 99, No. 3, 390– 403 0021-9010/14/$12.00 http://dx.doi.org/10.1037/a0030264

390

Theoretical Development

Leadership in Virtual Teams

There is consensus among scholars that virtual teams are more

difficult to lead than face-to-face teams (Bell & Kozlowski, 2002;

Duarte & Snyder, 2001;Gibson & Cohen, 2003;Hinds & Kiesler,

2002;Lipnack & Stamps, 2000). As a consequence of the lack of

face-to-face contact and geographical dispersion, as well as the

(often) asynchronous nature of communication, it is more difficult

for team leaders to perform traditional hierarchical leadership

behaviors such as motivating members and managing team dy-

namics (Avolio et al., 2000;Bell & Kozlowski, 2002;Purvanova

& Bono, 2009). It has been argued that leader influence can be

extended by having leadership augmented by new media (Avolio

& Kahai, 2003;Avolio et al., 2000) and that team leaders simply

have to learn how to use and apply those media properly. Findings

from empirical research show that getting virtual teams to function

equivalently to face-to-face teams requires virtual team leaders to

invest much more time and effort (Purvanova & Bono, 2009),

although showing more initiative, trying harder, and investing

more time and energy might not always be feasible.

Some scholars suggest that leadership functions should be sup-

plemented by providing structural supports (Bell & Kozlowki,

2002;Hinds & Kiesler, 2002;Kahai, Sosik, & Avolio, 2003). For

example, structuring rewards to provide incentives for perfor-

mance should result in higher motivation. Another suggested ap-

proach is to supplement leadership by distributing leadership to

team members (Bell & Kozlowski, 2002). Sharing leadership with

team members is based on the premise that leadership should not

be the sole responsibility of a hierarchical leader, but should be

collectively exercised by empowering and developing individual

team members (Kirkman, Rosen, Tesluk, & Gibson, 2004).

Although this view of leadership challenges in virtual teams has

consensus in the literature, it has not been subjected to empirical

verification. With respect to improving team performance, it is

important to understand the extent to which the influence of

hierarchical leadership is attenuated (or not) as team virtuality

increases. Moreover, if the influence of hierarchical leadership is

diminished as is suspected, then the extent to which it can be

supplemented by structural supports and shared team leadership

(and, potentially, other supplements) becomes a critical target for

theory and research extensions.

To examine these issues, our conceptual model treats hierarchi-

cal leadership, structural supports, and shared team leadership as

inputs to team performance. The model is illustrated in Figure 1.

The basic premise of our approach is that supplementing hierar-

chical leadership with shared leadership and structural supports

will be more relevant when teams are more virtual in nature. Thus,

the degree of team virtuality is predicted to moderate the relation-

ships between hierarchical leadership, structural supports, and

shared team leadership with team performance.

There are two notable aspects of the model. First, it is focused on

the contribution of these input factors to team performance. The

model does not focus on mediating processes at this stage of the

research. The primary reason for this focused approach is to enable a

clear evaluation of the moderating effects of virtuality on the contri-

butions of hierarchical leadership, structural supports, and shared

leadership to team performance. Second, the inputs are conceptual-

ized as distinct higher-order factors or construct composites, rather

than unitary constructs. This allows each of the inputs to be concep-

tualized as a composite of established constructs. For example, hier-

archical leadership is represented by transformational leadership,

leader–member exchange, and supervisory mentoring. Each of these

constructs, as core aspects of hierarchical leadership, is supported by

a body of theory and empirical research with established measures.

Using established constructs and measures of hierarchical leadership

as input factors allows us to clearly assess the potential supplementary

influence provided by structural supports and shared leadership. The

same conceptual and measurement approach using established con-

structs and measures is applied to structural supports and shared

leadership.

Team Virtuality

With the growth and evolution of virtual teams during the past

decade, researchers have focused on the conceptualization and

measurement of team virtuality (e.g., Bell & Kozlowski, 2002;

Hinds, Liu, & Lyon, 2011;Kirkman & Malthieu, 2005). In early

research, virtuality was treated as distinctly categorical; research-

ers applied a simple dichotomous characterization of virtual and

face-to-face teams. More recently, however, scholars have asserted

that this simple characterization glosses over a variety of nuanced

dimensions that underlie a range of differences in the degree of

virtuality (Gibson & Gibbs, 2006;Irwin & McClelland, 2003;

Kirkman et al., 2012;MacCallum, Zhang, Preacher, & Rucker,

2002;Mesmer-Magnus et al., 2011). Whereas early conceptual-

izations focused exclusively on geographic distribution, subse-

quent conceptualizations added electronic communication and

noted differences between the use of asynchronous and synchro-

nous communications (e.g., Bell & Kozlowski, 2002). Empirical

research, accordingly, refers to both the facets of geographic distri-

bution (e.g., O’Leary & Cummings, 2007;O’Leary & Mortensen,

2010) as well as the relative amount of e-communication media usage

(Griffith, Sawyer, & Neale, 2003;Kirkman et al., 2004;Mesmer-

Magnus et al., 2011) as indicative of “team virtuality.” This is now

the established approach to conceptualizing virtuality.

Structural Supports

Hierarchical Leadership

Shared Team Leadership

•Reward Systems

•Communication and

Information

•Transformational Leadership

•Leader-Member Exchange

•Career Mentoring

•Cognitive Team Learning

•Affective Team Support

•Behavioral Member-

Member Exchange

Team Performance

Team

Virtuality

•Geographic

Distribution

•Electronic Communication

•Cultural

Background

Figure 1. Effects of structural supports, hierarchical leadership, and

shared team leadership in predicting team performance, moderated by team

virtuality.

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

391

LEADING VIRTUAL TEAMS

However, virtual teams increasingly span national boundaries

and differences in cultural background are becoming more impor-

tant to consider as an aspect of virtuality (Hinds et al., 2011;

Staples & Zhao, 2006;Tsui, Nifadkar, & Ou, 2007). Indeed, Hinds

et al. (2011) criticized the lack of inclusion of national and cultural

differences in conceptualizations of virtuality. As “organizations

are increasingly compelled to establish a presence in multiple

countries as a means of reducing labor costs, capturing specialized

expertise, and understanding emerging markets...they often

create conditions in which workers must collaborate across na-

tional boundaries” (Hinds et al., 2011, p. 136). Accordingly, re-

searchers need to put the global back into “global work” by

considering cultural differences.

Research is increasingly considering cultural differences as an

important component of virtuality in globally dispersed teams (e.g.,

Chen, Kirkman, Kim, Farh, & Tangirala, 2010;Gibson & Gibbs,

2006;Tsui et al., 2007). Based on this evolving view of virtuality, our

conceptualization comprises geographic distribution (e.g., O’Leary &

Cummings, 2007), relative amount of e-communication media usage

(e.g., Kirkman et al., 2004), and cultural diversity (e.g., Gibson &

Gibbs, 2006;Hinds et al., 2011;Tsui et al., 2007) as an addition to the

established components of team virtuality.

The Role of Hierarchical Leadership in Virtual Teams

Hierarchical leadership reflects formally designated leadership

(Ensley, Hmieleski, & Pearce, 2006;Morgeson, DeRue, & Karam,

2010;Yukl, 2010). Two well-established leadership theories rel-

evant to hierarchical leadership that have been widely supported in

the empirical literature are transformational leadership and leader–

member exchange (LMX). Both transformational leadership

(Fuller, Patterson, Hester, & Stringer, 1996;Judge & Piccolo,

2004;Lowe, Kroeck, & Sivasubramaniam, 1996) and LMX (e.g.,

Gerstner & Day, 1997;Graen & Uhl-Bien, 1995) are strong

predictors of individual and team performance. Moreover, trans-

formational leadership and LMX are the most prevalent ap-

proaches used in research on virtual teams (e.g., Avolio et al.,

2000;Hambley, O’Neill, & Kline, 2007;J. M. Howell & Hall-

Merenda, 1999;J. M. Howell, Neufeld, & Avolio, 2005).

Although it has received less attention, we posit that supervisory

career mentoring (e.g., Kram, 1985) is an important leadership

technique in virtual teams. Supervisory career mentoring is related

to career outcomes such as salary level, promotion rate, and job

satisfaction, as well as to objective and subjective performance

(Allen, Eby, Poteet, Lentz, & Lima, 2004;Chao, Walz, & Gardner,

1992;Scandura & Ragins, 1993;Whitely, Dougherty, & Dreher,

1991). Transformational leadership, LMX, and supervisory career

mentoring are the three primary constructs that comprise hierar-

chical leadership in the model.

First, transformational leadership (e.g., Bass, 1985,1998) has

been found to enhance performance in a wide range of organiza-

tional settings (Fuller et al., 1996;Judge & Piccolo, 2004;Lowe et

al., 1996). Transformational leader behaviors are aimed at inspir-

ing follower motivation and stimulating them to stretch their

capabilities and to go beyond typical performance (Judge & Pic-

colo, 2004). However, these forms of leader behavior have also

been posited to have weaker relations for virtual teams (Hambley

et al., 2007;J. M. Howell & Hall-Merenda, 1999;J. M. Howell et

al., 2005). Interpretations of leader behavior as transformational

are likely facilitated by cues that are more difficult to transmit,

detect, and interpret in a virtual work context.

Second, LMX also contributes to positive organizational out-

comes (Gerstner & Day, 1997;Graen & Uhl-Bien, 1995). LMX is

concerned with the nature and the quality of the dyadic relation-

ship between the team leader and each member. It describes the

nature of the leader–member relationship and, as such, is primarily

developed through face-to-face contact (Gerstner & Day, 1997),

although it can be maintained via forms of electronic communi-

cation such as e-mail and video-conferencing. LMX provides an

alternative mechanism for leader influence (J. M. Howell & Hall-

Merenda, 1999) since interpersonal relationships, once developed,

might be less adversely affected by the lack of ongoing face-to-

face contact in virtual teams, but may also be difficult to develop

where the leader has little to no face-to-face contact with team

members.

Third, Hamilton and Scandura (2003) highlighted e-mentoring

as an important leadership function for managing virtual teams,

since it is not restricted to face-to-face contact. Moreover, due to

virtual interaction, demographic “cues” (e.g., age or gender) are

less salient and less likely to influence protégé selection. Accord-

ingly, decisions about who to mentor will be more likely based on

performance criteria. Mentoring further aids in the development of

strong personal relationships that help strengthen leader influence

on the team member (Ostroff & Kozlowski, 1993). By increasing

interaction among leaders and members, it can counteract the

negative effects of limited face-to-face contact in virtual teams

(Hamilton & Scandura, 2003).

Hypothesis 1: The positive relationship between hierarchical

leadership (transformational leadership, LMX, and mentoring)

and team performance decreases as team virtuality increases.

The Role of Structural Supports in Virtual Teams

Given that hierarchical leadership is assumed to be more diffi-

cult in virtual teams, it is then important to understand how

hierarchical leadership can be supplemented when teams are more

virtual in nature. Structural supports represent a form of indirect

influence, where influence on the motivation and behavior of team

members takes place via structural attributes (Bell & Kozlowski,

2002;Wunderer, 2002). Structural supports draw from the leader-

ship substitutes approach (Kerr, 1977;Kerr & Jermier, 1978),

which asserts that aspects of the organization and task structure

can compensate, enhance, or neutralize the effects of leadership on

employee behavior. While originally proposed as a moderating

variable (J. P. Howell & Dorfman, 1981,1986), empirical and

meta-analytic studies have found strong support for main relation-

ships of structural and compensating variables with team outcomes

(Podsakoff, MacKenzie, & Bommer, 1996). Structural factors

have been suggested by Bell and Kozlowski (2002) as a supple-

ment for virtual team leadership, which is consistent with structural

functions listed by other scholars who refer to managing information,

resources, and material rewards (e.g., Fleishman et al., 1991).

In virtual teams, the stability and reduction of ambiguity pro-

vided by structural supports may compensate for the turbulence

and unpredictability that characterizes virtual teamwork (Zaccaro

& Bader, 2003;Zigurs, 2003). Bell and Kozlowski (2002) argued

that because of the geographic dispersion of virtual teams, an

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

392 HOCH AND KOZLOWSKI

important function of leadership is to create structures and routines

that substitute for direct leadership influence and regulate team

behavior. Consistent with research that suggests structural supports

have direct relationships with outcomes that supplement hierarchi-

cal leadership (Podsakoff et al., 1996), our model conceptualizes

them as having a direct relationship rather than a moderating one.

Virtual team members usually work on virtual teams in addition

to their line function and research has highlighted the importance

of rewarding virtual team members for both aspects. Geographical

dispersion can result in a lack of motivation to focus on virtual

team responsibilities, makes monitoring of virtual team members

difficult, and also creates higher levels of anonymity (Kiesler &

Cummings, 2002;Wiesenfeld, Raghuram, & Garud, 1999). Fur-

ther, reward systems need to be fair, such that individual employ-

ees perceive they are being rewarded according to their inputs

(e.g., effort, time, performance, etc.) on their virtual team work

(Colquitt, 2004;Dulebohn & Martocchio, 1998;Schminke, Cro-

panzano, & Rupp, 2002). Being rewarded in a fair and transparent

way for the work performed on the virtual team will lead employ-

ees to put more efforts toward virtual teamwork.

Second, a major component of structural supports is the com-

munication and information management systems used for virtual

teams. Building and managing communication and information

management systems that facilitate connectivity, remove percep-

tions of distance, and facilitate the organization and accessibility of

information can reduce feelings of lack of trust, anonymity, de-

individuation, and perceptions of low social control. In addition,

virtual teamwork is typically white-collar, knowledge based, in-

tellectual, and interdependent. The management of communication

and information is central to cognitive tasks (Clampitt & Downs,

2004;Faraj & Sproull, 2000). Thus, a key aspect of performance

in virtual teams is managing the “triangle” of factors: shared

knowledge (in changing and flexible organization structure), via

electronic communication systems, and with experts as primary

collaborators (Griffith et al., 2003;Kanawattanachai & Yoo, 2007;

Malhotra & Majchrzak, 2004). As a form of structural support,

managing communication and information flow (Fleishman et al.,

1991) include information infrastructure and quality of informa-

tion received, as well as the transparency and adequacy of

communication and information management. Communication

and information management are posited to influence virtual

team performance. We expect that team virtuality moderates the

relationship between structural supports and team performance.

Specifically,

Hypothesis 2: The positive relationship between structural

supports (reward systems; communication and information)

and team performance increases as team virtuality increases.

The Role of Shared Team Leadership in Virtual

Teams

Shared team leadership describes a mutual influence process,

characterized by collaborative decision-making and shared respon-

sibility, whereby team members lead each other toward the

achievement of goals (Day, Gronn, & Salas, 2004;Pearce &

Conger, 2003). Shared team leadership is presumed to create

stronger bonds among the team members; facilitate trust, cohesion,

and commitment; and mitigate disadvantages of virtual teams

(Pearce & Conger, 2003). Thus, sharing leadership functions with

team members provides a mechanism to supplement hierarchical

leadership in virtual teams (Bell & Kozlowski, 2002;Pearce, Yoo,

& Alavi, 2004;Tyran, Tyran, & Shepherd, 2003).

Scholars have argued that shared leadership is a more appropri-

ate form of team leadership than hierarchical leadership repre-

sented by the solo leader (Brown & Gioia, 2002;Day et al., 2004;

Yukl, 2010). Reasons for this include the notion that team member

communication is less formal and less hierarchically based, and,

therefore, team members can more easily overcome communica-

tion difficulties (Bell & Kozlowki, 2002;Pearce et al., 2004). In

addition, work processes in virtual teams are characterized as

cognitively loaded, highly interdependent, yet autonomous. Com-

plex teamwork requires the use of self-managing teams (Bell &

Kozlowski, 2002;Pearce, 2004;Pearce & Manz, 2005). Team

self-management and empowerment, in this context, has been

shown to enhance virtual team performance in a sample 35 sales

and service virtual teams in a high-technology organization (Kirk-

man et al., 2004).

There is no “one best way” to measure shared leadership. The

concept is in its infancy (Avolio, Jung, Murry, & Sivasbramaniam,

1996;Carson, Tesluk, & Marrone, 2007;Mayo, Meindl, & Pastor,

2003;Mehra, Smith, Dixon, & Robertson, 2006;Pearce & Conger,

2003), and, thus, a challenge facing researchers is determining how

to measure shared team leadership. One primary approach has

simply treated shared team leadership as analogous to hierarchical

leadership, but conceptualized at the team level of analysis (e.g.,

Avolio et al., 1996;Bowers & Seashore, 1966;Pearce & Sims,

2002). This approach assesses shared leadership as collective

concept in the form of traditional leadership behaviors (e.g., trans-

formational leadership) that are performed by team members.

Typically, a traditional leadership measure—like transformational

leadership—is referenced to the team as a collective (reference

shift model; Chan, 1998; e.g., “Our team engages in behaviors that

help create a team vision”) to comprise shared team leadership.

However, consistent with other researchers (Carson et al., 2007;

Mayo et al., 2003;Mehra et al., 2006), we do not conceptualize

shared team leadership as parallel with hierarchical leadership.

Team members do not need to necessarily perform the same kind

of leadership behaviors as their supervisors (Künzle et al., 2010;

Morgeson et al., 2010) in order to engage in shared leadership.

Rather, shared leadership can be conceptualized as the extent to

which team members behave in ways to prompt the team processes

that underlie team performance. Team process researchers have

distinguished cognitive, affective-motivational, and behavioral

functions as keys to team effectiveness (Kozlowski & Bell, 2003;

Kozlowski & Ilgen, 2006). Team leader effectiveness, as outlined

in functional leadership (McGrath, 1962), is based on leaders

addressing the cognitive, affective, and behavioral functioning of

their teams (Zaccaro, Rittman, & Marks, 2001). These leadership

functions can be performed through informal leadership mecha-

nisms (Morgeson et al., 2010) such as shared team leadership.

In capturing shared leadership in virtual teams, affective-

motivational functions can be represented in terms of perceived

team support, which is related to building trust and team cohesion

(Kasper-Fuehrer & Ashkanasy, 2001) and may compensate for

specific gaps resulting from the lack of face-to-face meetings in

virtual teams, that is, lack of trust, and higher levels of anonymity

(Jarvenpaa, 2004;Jarvenpaa & Leidner, 1999). Cognitive func-

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

393

LEADING VIRTUAL TEAMS

tioning can be represented in terms of team learning (Edmondson,

1999;Edmondson, Bohmer, & Pisano, 2001), which is highly

relevant due to the cognitively loaded nature of work in virtual

teams. For behavioral processes, member–member exchange qual-

ity (Sherony & Green, 2002), which reflects the application of

traditional leader–member exchange (Gerstner & Day, 1997;

Graen, 1976;Graen & Uhl-Bien, 1995;Seers, 1989) to lateral

coworker exchange (i.e., among peers), is expected to be important

(Baltes, Dickson, Sherman, Bauer, & LaGanke, 2002;Hollings-

head & McGrath, 1995). We expect that shared team leadership

will provide a means to compensate for the gaps and disadvantages

in virtual teams such that it will be more strongly related to team

performance with increasing levels of virtuality. Specifically,

Hypothesis 3: The positive relationship between shared team

leadership (cognitive, affective, and behavioral leadership)

and team performance increases as team virtuality increases.

Method

Sample

Study participants were comprised of 565 team members and

team leaders on 101 research and development (R & D) teams

from global manufacturing industries. Human resource leaders in

several companies were contacted. A number agreed on company

participation in the study and facilitated data collection in ex-

change for technical report feedback and personal debriefing on

the teams. The teams were similar in that all participants worked

onR&Dprojects that involved knowledge-based, interdependent

group tasks. All teams worked under some degree of virtuality.

That is, they worked across geographic distance, across different

time zones, with employees from different cultural backgrounds,

and primarily used electronic communication media for their work.

However, the degree of virtuality among the teams varied. While

some of them worked primarily face-to-face and to a limited

degree virtually, others ranged widely in the degree to which they

operated virtually. All of the teams primarily used electronic

communication media for their work, although some teams were

distributed across up to seven sites per team, whereas others pri-

marily worked at one site. Team members on virtual teams worked on

average 359.20 miles away from each other, and 12% of the virtual

team members worked alone at one site.

Teams consisted of an average of five members (SD ⫽2.94,

range ⫽3–13). The average tenure of team members was 4.18

years (SD ⫽4.96), and the average tenure of the leaders was

4.23 years (SD ⫽4.97). The average age of the team members was

37 years (SD ⫽6.17, range ⫽19–61 years). Team members

averaged working on five projects at the same time (M⫽4.86,

SD ⫽18.51). Since they were developing products together, their

work was interdependent. Therefore, task interdependence was

measured as a control. Teams consisted of 77.1% male employees.

Average team leader age was 41 years (SD ⫽8.42, range ⫽25–61

years), and 89.1% of the team leaders were male.

Measures

Scales. All constructs in the model center on the team as the

focal unit of theory. Accordingly, all measures were specified at

the team level (i.e., team referents using a reference shift model of

composition; Chan, 1998). Furthermore, all items were framed with

respect to virtual team performance. The introduction of every page of

the questionnaire stated: “Please respond to all items with regard to

your work on your virtual team and not your regular line function,” or

“please respond to all of the following items with respect to your work

on your virtual team.” Team members rated leadership and team

composition. Team leaders rated the team’s performance. All of those

items were measured using a 5-point Likert scale ranging from 1

(strongly disagree)to5(strongly agree).

Hierarchical leadership was assessed using three indicators

rated by team members. Transformational leadership was mea-

sured with the Multifactor Leadership Questionnaire (MLQ) 5X

(Avolio & Bass, 2004). Twenty items were used to measure

transformational leadership with its five subscales of attributed and

behavioral idealized influence, intellectual stimulation, inspira-

tional communication, and individual consideration. A sample

item for inspirational communication was “My team leader talks

optimistically about the future.” Cronbach’s ␣was .92. Leader–

member exchange (LMX) was measured using a scale developed

by Graen, Novak, and Sommerkamp (1982; Wayne, Shore, &

Liden, 1997). A sample item was “My supervisor understands my

problems and needs.” Cronbach’s ␣was .89. Supervisor career

mentoring was measured by a validated scale (Blickle & Bou-

jataoui, 2005;Noe, 1988) based on the career support scale by

Riley and Wrench (1985) that assessed three dimensions: career

support, socio-emotional support, and role model. A sample item

is “My supervisor assigns tasks to me that foster the direct contact

with important supervisors.” Cronbach’s ␣was .89.

Structural supports were measured by (1) reward management and

(2) information and communication management, with one or two

subscales each. Reward management was measured using a scale to

assess the quality of reward systems and a scale for fairness of reward

systems. First, organizational reward management was measured

using five items from Podsakoff and MacKenzie (1994). A sample

item was “My performance appraisal system is very motivating.”

Cronbach’s ␣was .86. Second, a nine-item scale was used to

measure the fairness, transparency, and accountability of reward

systems based on Schminke et al. (2002). Specifically, items mea-

sured the three dimensions of performance evaluation, pay, and pro-

motion systems with regard to the extent they were perceived as (a)

fair, (b) accurate, and (c) transparent. Two sample items were “My

performance appraisal systems is fair,” “. . . transparent,” and so forth.

Cronbach’s ␣was .87.

Information and communication management comprised five

items adapted from Clampitt and Downs (2004) assessing the

Information Quality,orQuality of Information Received. A sample

item was “Information that I receive is often unclear and not

precise” (R). Cronbach’s ␣of this scale was .79. It also assessed

the extent to which Information Coordination Quality with a scale

adapted from Faraj and Sproull (2000). A sample item was: “There

is seldom confusion about how to accomplish our task.” Cron-

bach’s ␣was .87.

Shared leadership was measured in terms of cognitive, affec-

tive, and behavioral dimensions (Kozlowski & Bell, 2003;Koz-

lowski & Ilgen, 2006;Zaccaro et al., 2001). Specifically, cognitive

processes were measured with four items on team learning to

assess the extent to which team members are active in obtaining

feedback to improve their own performance. Here, a sample item

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

394 HOCH AND KOZLOWSKI

is “Our team actively searches our own performance for deficits.”

Cronbach’s ␣was .92. Next, affective correlates were measured

with five items on perceived team support (PTS), which had been

developed on the basis of the perceived organizational support

construct by Eisenberger, Huntington, Hutchison, and Sowa

(1986) and previously used by Wayne et al. (1997;Bishop, Scott,

& Burroughs, 2000). PTS measures the extent to which team

members support each other. A sample item is “My team really

cares about my well-being.” Cronbach’s ␣was .87. Finally, be-

havioral shared team leadership, in terms of member–member

exchange (MMX) was measured with items that applied the leader–

member exchange construct to the team consistent with Sherony

and Green (2002). Specifically, following a referent shift approach

(Chan, 1998), to measure MMX we referenced LMX-7 items (e.g.,

traditional measure of leader–member exchange; e.g., Gerstner &

Day, 1997;Graen & Uhl-Bien, 1995) to the team. A sample item

is “My team understands my problems and needs.” Cronbach’s ␣

was .87.

Team performance was rated by team leaders on a scale based

on Hoegl and colleagues (Gemuenden & Hoegl, 2001;Hoegl &

Gemuenden, 2001). The team leader rated the team’s performance

regarding the aspects of work quantity, quality, keeping within the

project schedule, and keeping within the budget using a scale

ranging from 0% to 100%. Cronbach’s ␣was .79.

Team virtuality. The degree of team virtuality was measured

in terms of three indicators: geographic dispersion, electronic

communication media usage, and cultural differences (Fiol &

O’Connor, 2005;Gibson & Cohen, 2003;Gibson & Gibbs, 2006;

Kirkman & Malthieu, 2005;Kirkman et al., 2004;Townsend,

DeMarie, & Hendrickson, 1998). Geographic dispersion was as-

sessed with a measure by O’Leary & Cummings (2007), which

included seven indicators, such as distance in miles, number of

sites per team, percentage of team members alone at one site, and

others. The relative amount (frequency) of electronic versus face-

to-face communication was measured with a scale based on Kac-

mar, Witt, Zivnuska, and Gully (2003) that included indicators of

e-mail, chat, video and telephone conferencing, text and instant

messaging, and face-to-face meetings that were rated with

respect to frequency of use for communicating with colleagues

and supervisors. Since we were interested in the relative fre-

quency of electronic communication media use relative to total

communication, we calculated a ratio of relative communica-

tion frequency by dividing the sum of the electronic communi-

cation media use by the sum of all communication (media and

face-to-face communication). To account for cultural differ-

ences, we averaged the number of different nationalities per

team. The number of nationalities per teams on average was

3.60 (SD ⫽8.02) nationalities per team.

The three scores of geographic distribution, electronic media

usage, and cultural differences (nationalities per team) were sub-

ject to a z-transformation and were summed to form the team

virtuality composite. Cronbach’s ␣was .77. The measure ranged

from –3.80 to 16.17, with M⫽–0.32, and SD ⫽3.57. Higher

scores indicate increased virtuality.

Analyses

Hypothesis testing was conducted in a three-step procedure.

First, we conducted confirmatory factor analyses (CFA; Arbuckle,

2003) on the individual level data to assess the fit of the measure-

ment model for the input factors and for the virtuality moderator

composite. We accounted for the two-level hierarchical structure

of the inputs, with the construct measures specified to load onto

their respective input variables. CFA also supported the two-level

hierarchical structure of the virtuality moderator (i.e., geographical

distance combined with e-communication, and culture sub-

factors). Second, the main analyses were performed on group level

data. Given the reduction in sample size, we used partial least

squares structural equation modeling (PLS), a regression-based

structural equation model (SEM) that is robust with regard to small

samples (Chin, 2001;Ringle, Wende, & Will, 2006), which has

been adopted by many team researchers (Jung & Sosik, 2002;

Sambamurthy & Chin, 1994;Sosik, Avolio, & Kahai, 1997). Tests

of significance in PLS were conducted using the bootstrap re-

sampling procedure (Efron & Tibshirani, 1993). Third, we tested

moderation effects by computing the interaction terms between

team virtuality and the input variables using centered data follow-

ing Aiken and West (1991).

Justification for aggregation. The theoretical focus of the

virtual team leadership model is specified at the team level. As-

sessments of the input variables were obtained from individual

team members using team referent items, which conforms to a

referent shift composition model (Chan, 1998) for data aggrega-

tion. Thus, we examined restricted within-group variance for all

variables prior to aggregation to the team level of analysis (Klein

et al., 2000;Kozlowski & Klein, 2000). We calculated ICC1,

which is an index of inter-rater reliability, and ICC2, which is an

index of the stability of the aggregated mean for each measure

(Bliese, 2000). On average, across measures, the ICC1 was .45,

and ICC2 was .69 (following r-to-zconversion). Specifically, the

ICC1 and ICC2, respectively, were as follows: organizational

reward management was .44 and .75, reward systems was .44 and

.77, the quality of the information received was .46 and .67, the

way the knowledge was coordinated was .46 and .76, transforma-

tional leadership was .43 and .81, LMX was .43 and .83, mentoring

was .35 and .82, team learning was .43 and .80, perceived team

support (PTS) was .44 and .83, and member–member exchange

(MMX) was .39 and .83. Overall, the ICC1 indices were substan-

tial (Bliese, 2000), providing evidence to support aggregation, and

the ICC2 values indicated stability for the aggregated mean

(Bliese, 2000).

Control variables. Since team age and gender composition

correlated with several of the study variables, analyses were per-

formed controlling for gender and age. We further controlled for

task interdependence (three items, based on Van Der Vegt, Emans,

& Van De Vliert, 2000; Cronbach’s ␣⫽.77) and the number of

projects an employee was working on (“How many projects are

you working on at the same time?”). We entered all five variables

as controls into the PLS model.

Results

Means, standard deviations, inter-correlations, and reliability

coefficients of study variables are presented in Table 1.

Pre-Analyses

A CFA for the measurement model structure of the inputs was

performed. In order to determine if all the scales loaded on a single

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

395

LEADING VIRTUAL TEAMS

factor (representing a lack of distinction among the input factors),

we first tested a one-factor model. This did not fit the data well

(␹

/df ⫽2.68, comparative fit index [CFI]⫽.89). Next, we

computed a three-factor model, where hierarchical leadership,

structural supports, and shared team leadership were specified as

three separate constructs with all items loading on either hierar-

chical leadership, the structural supports, or the shared team lead-

ership construct. This three-factor model had a better fit (␹

/df ⫽

1.53, CFI ⫽.96) and was a significant improvement compared to

the one-factor model, ⌬␹

(2) ⫽2,180.92. Analyses were con-

ducted using modification indices calculations (Buehner, 2004).

We then examined a hierarchically structured three-factor model,

where each item loaded first on their respective facet (i.e.,

transformational, LMX, mentoring, reward systems, extrinsic

motivation, information quality, information coordination, process

improvement, MMX, PTS). These 10 facets each formed the

second-order, hierarchical constructs for hierarchical leadership,

structural supports, or shared team leadership. The second-order

constructs of hierarchical leadership, structural supports, and

shared team leadership were allowed to intercorrelate. This

second-order, hierarchical model provided a good fit to the data

(␹

/df ⫽1.18, CFI ⫽.99, root-mean-square error of approxima-

tion [RMSEA]⫽.02). Specifically, it demonstrated a better fit than

the previously tested three-factor, non-hierarchical model,

⌬␹

(10) ⫽1,300.94, p⬍.001, and therefore provided the best fit

for the theoretically expected factor structure. As a further indica-

tor for the quality of the measurement model, in PLS, the AVE-

score (Fornell & Larcker, 1981) was calculated. The AVE-score

assesses the percentage of variance among the indicators caused by

the latent variable in relation the measurement error. The AVE-

score should exceed .5. In the model we tested, the total AVE-score

was .85, which supports the quality of the measurement model.

The measurement model findings provide support for our approach

to use established constructs, validated measures, and composites

to represent the conceptual structure for the inputs.

We next used CFA to evaluate the structure of the virtuality

composite. Researchers have generally treated geographic distance

and the use of electronic communication media as key components of

virtuality (e.g., Gibson & Cohen, 2003;Griffith et al., 2003;Kirkman

et al., 2004;Mesmer-Magnus et al., 2011;O’Leary & Cummings,

2007;O’Leary & Mortensen, 2010). With the rise of globalization,

however, some theorists have made a conceptual case for incorporat-

ing cultural differences into the conceptualization of team virtuality

(Hinds et al., 2011;Kirkman & Malthieu, 2005;Staples & Zhao,

2006;Tsui et al., 2007). Our composite conceptualization is consistent

with this emerging perspective. Thus, we used CFA to evaluate the

efficacy of this approach. We compared five models composed of the

three virtuality components:

1. a one-factor structure (i.e., all items loading on one

factor);

2. our composite—a one-factor hierarchical model with two

sub-factors (i.e., electronic communication media com-

bined with geographic dispersion; and nationality);

3. two separate factors (i.e., electronic media communication

combined with geographic dispersion; and nationality);

Table 1

Means, Standard Deviations, and Pearson Correlation Coefficients

Variable MSD 1234 5 67891011121314151617

1. Age 37.22 6.16 —

2. Gender

1.33 0.35 .04 —

3. Team size 5.36 2.97 ⫺.10 ⫺.12 —

4. Nationalities/team 3.60 8.02 ⫺.26

ⴱⴱ

.03 .08 —

5. Geographic dispersion 0.14 3.70 ⫺.34

ⴱⴱ

⫺.14 .05 .38

ⴱⴱ

—

6. Relative e-communication (Inv.) 3.59 1.30 .12 .07 ⫺.02 ⫺.34

ⴱⴱ

⫺.33

ⴱⴱ

—

7. Reward systems 2.88 0.74 .02 .01 ⫺.10 ⫺.10 ⫺.05 .20

ⴱ

.87

8. Extrinsic motivation 2.71 0.96 .07 .15 .10 .05 ⫺.16 ⫺.01 .51

ⴱⴱ

.86

9. Information quality 2.42 0.58 .11 .01 ⫺.02 ⫺.21

ⴱ

⫺.11 .13 .35

ⴱⴱ

⫺.13 .79

10. Coordination 3.60 0.71 .22

ⴱ

⫺.08 ⫺.05 ⫺.31

ⴱⴱ

⫺.19 .06 .28

ⴱⴱ

.06 .49

ⴱⴱ

.87

11. Transformational 3.21 0.58 ⫺.13 ⫺.03 .10 ⫺.16 .08 .23

ⴱ

.24

ⴱ

.09 .21

ⴱ

.28

ⴱⴱ

.92

12. LMX 3.93 0.67 ⫺.02 ⫺.07 .13 ⫺.18 ⫺.01 .27

ⴱⴱ

.39

ⴱⴱ

.20

ⴱ

.32

ⴱⴱ

.41

ⴱⴱ

.72

ⴱⴱ

.89

13. Mentoring 2.79 0.67 ⫺.17 ⫺.10 .12 .02 .22

ⴱ

.16 .41

ⴱⴱ

.26

ⴱⴱ

.11 .17 .68

ⴱⴱ

.70

ⴱⴱ

.89

14. PTS 3.14 0.52 .05 .03 .09 ⫺.08 .08 ⫺.04 .01 .04 .03 .29

ⴱⴱ

.32

ⴱⴱ

.26

ⴱⴱ

.25

ⴱⴱ

.87

15. MMX 3.80 0.59 ⫺.07 ⫺.15 .10 ⫺.10 ⫺.06 .11 .22

ⴱ

.16 .24

ⴱ

.50

ⴱⴱ

.39

ⴱⴱ

.43

ⴱⴱ

.26

ⴱⴱ

.63

ⴱⴱ

.87

16. Process feedback 3.20 0.76 ⫺.06 ⫺.06 ⫺.02 ⫺.01 .11 ⫺.04 .23

ⴱ

.13 .11 .44

ⴱⴱ

.31

ⴱⴱ

.29

ⴱⴱ

.27

ⴱⴱ

.52

ⴱⴱ

.50

ⴱⴱ

.92

17. Team Performance

89.45 9.41 ⫺.05 .11 ⫺.18 ⫺.10 ⫺.09 ⫺.04 .09 .12 .19 .31

ⴱⴱ

⫺.12 .13 ⫺.09 .09 .18 .05 .79

Note. N ⫽101 teams. LMX ⫽leader–member exchange; PTS ⫽perceived team support; MMX ⫽member–member exchange.

Gender: 1 ⫽male; 2 ⫽female.

Leader-rated variable.

ⴱ

p⬍.05.

ⴱⴱ

p⬍.01.

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

396 HOCH AND KOZLOWSKI

4. a one-factor hierarchical model with three sub-factors (i.e.,

electronic communication media, geographic dispersion,

and nationality) to represent separate contributions to a

higher-order factor; and

5. three separate factors (i.e., electronic communication media,

geographic dispersion, and nationality).

As shown in Table 2, results indicated that Model 2, the hier-

archical one-factor model with two sub-factors (which reflected

our composite conceptualization) provided the best fit to the data.

Model 1, the one-factor model with no sub-factors, did not fit the

data very well (␹

/df ⫽1.91, goodness-of-fit index [GFI]⫽.85,

CFI ⫽.93, RMSEA ⫽.10). Fit for Model 2 (␹

/df ⫽1.39, GFI ⫽

.89, CFI ⫽.97, RMSEA ⫽.06) was good. Fit for Model 2 was

significantly better than for Model 1, the one-factor model,

⌬␹

(3) ⫽48.27, p⬍.001, or for Model 3, the two-factor non-

hierarchical model, ⌬␹

(1) ⫽23.85, p⬍.001. Model 2 also fit the

data better than Model 5, the three-factor model, ⌬␹

(14) ⫽29.58,

p⬍.01, which showed poor fit overall (␹

/df ⫽1.85, GFI ⫽.84,

CFI ⫽.93, RMSEA ⫽.09). Thus, there was good empirical

support for our conceptualization and composite approach to cap-

turing team virtuality.

Main Analyses: Inner Model Analyses

Next, we examined direct relationships via the inner (structural

model analyses) from PLS with the three groups of predictor

variables predicting team effectiveness on the team level data. The

inner model analyses showed that both structural supports (b⫽

0.88, p⬍.01) and shared team leadership (b⫽1.80, p⬍.001)

predicted team performance, whereas hierarchical leadership did

not (b⫽0.85, ns). Those results are displayed in Table 3.

Moderation by Team Virtuality

Moderation analyses were conducted to determine whether the

degree of team virtuality had a differential influence on the rela-

tionship between the inputs and team performance as predicted by

the model. Centered data were used to compute the interaction

terms between team virtuality and the three groups of predictor

variables. When team virtuality was entered as a predictor, there

was a marginally negative relationship with team performance

(b⫽–0.40, p⬍.10), suggesting that with increasing levels of

team virtuality teams performed less well.

Next, hierarchical leadership interacted with team virtuality in

predicting team performance in a negative way (b⫽–1.74, p⬍

.01). With regard to structural supports, there was no longer a

significant main relationship with team performance (b⫽0.55, ns)

when team virtuality was added, but structural supports interacted

with virtuality in predicting team performance (b⫽2.77, p⬍

.001). Those results are displayed in Table 4.

As shown in Figures 2 and Figures 3, we graphed these rela-

tionships following Aiken and West (1991).Figure 1 shows that

under high levels of virtuality hierarchical leadership was not

related to team performance. Under low levels of virtuality, hier-

archical leadership was significantly related to team performance.

Figure 2 shows that structural supports were positively related to

team performance under high levels of virtuality, but not under low

virtuality. Hypotheses 1 and 2 were supported. Finally, for Hy-

pothesis 3, team virtuality did not interact with shared leadership

in predicting team performance (ns), whereas shared team leader-

ship was still positively related to team performance (b⫽1.94,

p⬍.001). Hypothesis 3 was not supported; results are displayed

in Table 4.

Discussion

Summary

This study examined the relationships between hierarchical

leadership, structural supports, and shared team leadership with

team performance, and the moderating effects of virtuality on these

relationships. Our research approach, which assessed each of the

inputs as construct composites, provided a measurement model

Table 3

Specifications of the Inner Model Path Coefficients of the

Distributed Leadership Model

Predictor variables

Team performance (supervisor rating)

bSDt

Hierarchical leadership 0.85 0.13 0.67

Structural supports 0.88

ⴱⴱ

0.04 2.24

Shared team leadership 1.80

ⴱⴱⴱ

0.04 2.23

Gender

0.96

ⴱⴱⴱ

0.03 3.89

Age ⫺1.33

ⴱ

0.04 3.39

No. of projects ⫺3.01

ⴱⴱⴱ

0.05 5.63

Task interdependence 0.96

ⴱ

0.03 2.12

.18

Note. N ⫽101 teams; Bootstrap 500: 2000.

Gender: 1 ⫽male; 2 ⫽female.

ⴱ

p⬍.05.

ⴱⴱ

p⬍.01.

ⴱⴱⴱ

p⬍.001.

Table 2

Model Comparisons for Measurement of Virtuality

Model ␹

/df GFI CFI RMSEA

1. One-factor model (without sub-factors) 1.91 .85 .93 .10

2. One-factor model with two sub-factors (hierarchical two-factor model) 1.39 .89 .97 .06

3. Two-factor model (non-hierarchical) 1.66 .87 .95 .08

4. One-factor model with three sub-factors (hierarchical three-factor model) 1.85 .84 .93 .09

5. Three-factor model (non-hierarchical) 1.85 .84 .93 .09

Note. N ⫽101. GFI ⫽goodness-of-fit index; CFI ⫽comparative fit index; RMSEA ⫽root-mean-square error of approximation.

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

397

LEADING VIRTUAL TEAMS

that exhibited a good fit to the data in our sample. With regard

direct relations, structural supports and shared leadership, but not

hierarchical leadership, were positively associated with team per-

formance. When testing for moderating effects, structural supports

were more, and hierarchical leadership was less, strongly associ-

ated with team performance, the higher the level of team virtuality.

The association between shared team leadership and team perfor-

mance was not affected by the degree of virtuality.

Theoretical Implications

The conceptualization and measurement of team virtuality.

First, central to virtual team leadership is the need to examine the

appropriate form of measurement to capture the multifaceted con-

cept of team virtuality. This is a primary contribution of our

research. The measure we developed incorporated the most recent

theorizing regarding the underpinnings of the virtuality construct;

it included geographic dispersion (O’Leary & Mortensen, 2010),

the relative amount of face-to-face and electronic communication

media usage (Griffith et al., 2003;Kirkman et al., 2004), and

cultural diversity (Hinds et al., 2011). With regard to cultural

diversity, our work reflects recent theorizing in the literature that

cultural differences add to virtuality (e.g., Chen et al., 2010;Hinds

et al., 2011;Tsui et al., 2007).

Leadership in virtual teams. The main goal of the present

research was to investigate hierarchical leadership in teams, the

inhibitory impact of virtuality on hierarchical leadership, and the

ability of structural supports and shared team leadership supple-

ment it. Our findings showed that the influence of hierarchical

leadership on team performance is weakened when teams are more

virtual in nature. Thus, when teams are virtual, it is desirable to

supplement the leader behaviors that are mitigated by distance,

electronic media, and cultural differences. Following Bell and

Kozlowski (2002), we examined the role of structural support

mechanisms and shared team leadership as alternative inputs to

team performance that could mitigate the loss of influence. Our

findings show that hierarchical leadership had weaker relations,

whereas structural supports were more strongly related, with

team performance under increasing levels of team virtuality.

Contrary to expectations, shared team leadership exhibited sta-

ble positive relations with team performance regardless of the

degree of virtuality.

Limitations and Research Extensions

Theorists have speculated that the processes of hierarchical

leadership are disadvantaged under conditions of virtuality, and

that supplements by structural supports and shared team leadership

can mitigate the loss of leadership influence (e.g., Bell & Kozlow-

ski, 2002). Our approach to examining this speculation was delib-

erately focused; we examined these factors as inputs to indepen-

dently rated team performance and treated them as construct

composites. Although this allowed a parsimonious examination of

the basic relationships of interest, it does not address the underly-

ing process mechanisms by which hierarchical leadership is inhib-

ited and structural supports provide supplements. Moreover, given

that shared team leadership exhibited a consistent relationship with

team performance regardless of the degree of virtuality, unpacking

the mechanisms by which it manifests this broad influence is

clearly in order.

There are some considerations that should be addressed in future

research to extend these findings. First, with moderation of the

low Structural

Supports

high Structural

Supports

Team Performance (In %)

low Virtuality

high Virtualit

Figure 3. Interaction between structural supports and team virtuality

predicting team performance.

Table 4

Moderation of Leadership Variables’ Effects by Team Virtuality

on Team Outcomes: Specification of Inner Model Path

Coefficients of the Distributed Leadership Model

Predictor

Team performance

(supervisor rating)

bSDt

Hierarchical leadership ⫺0.06 0.09 0.07

Hierarchical Leadership ⫻Team Virtuality ⫺1.74

ⴱⴱ

0.07 2.32

Structural supports 0.55 0.05 0.75

Structural Supports ⫻Team Virtuality 2.77

ⴱⴱⴱ

0.06 4.34

Shared team leadership 1.94

ⴱⴱⴱ

0.06 3.37

Shared Team Leadership ⫻Team Virtuality 0.70 0.09 0.78

Team virtuality ⫺0.40

†

0.07 0.89

Gender

1.16

ⴱⴱⴱ

0.03 3.21

Age ⫺1.59

ⴱⴱ

0.05 3.19

No. of projects ⫺3.01

ⴱⴱⴱ

0.06 5.45

Task interdependence 0.39 0.04 0.89

.27

Note. N ⫽101 teams; Bootstrap 500: 2,000 teams.

Gender: 1 ⫽male; 2 ⫽female.

†

p⬍.10.

ⴱⴱ

p⬍.01.

ⴱⴱⴱ

p⬍.001.

low Hierarchical

Leadership

high Hierarchical

Leadership

Team Performance (In %)

low Virtuality

high Virtualit

Figure 2. Interaction between hierarchical leadership and team virtuality

predicting team performance.

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

398 HOCH AND KOZLOWSKI

input factors to performance relationship by virtuality established,

the next increment should turn attention to the mediating mecha-

nisms that link the input factors with team performance. This will

necessitate longitudinal research designs to appropriately capture

the processes and minimize concerns about causal ambiguity.

Second, although common source method variance is not an issue

with respect to the relationship between the input factors and

performance (which was rated independently), it will be desirable

to distinguish inputs from mediating processes in future research.

This may be accomplished by cross-splitting teams to examine

relations between inputs and processes (e.g., Hofmann & Stetzner,

1996), although such designs necessitate large teams. With basic

input-output-moderation relations established, mediating pro-

cesses are obvious next steps for extension.

In addition, there are also issues surrounding the composite

approach used to capture the degree of team virtuality—which has

both advantages and disadvantages—that merit discussion. With

respect to advantages, the composite—which combines the facets

of geographical separation, use of electronic media, and cultural

diversity—is consistent with the conceptual evolution of the con-

cept of virtuality that has occurred over the last decade. Estab-

lished conceptualizations of virtuality focus on geographical sep-

aration and the use of electronic media (Gibson & Cohen, 2003;

Griffith et al., 2003;Kirkman et al., 2004;Mesmer-Magnus et al.,

2011;O’Leary & Cummings, 2007;O’Leary & Mortensen, 2010).

However, organizations have become increasingly multi-national,

work teams are more frequently dispersed around the world, and

technological interconnectivity continues to advance. By treating

the facets as a composite, we captured a richer conceptualization of

virtuality in a parsimonious fashion that was also empirically

supported in our data.

This conceptualization and assessment, however, also intro-

duces ambiguity with respect to the definition of virtuality and to

the precise contribution of the distinct components. Each compo-

nent is a unique characteristic, and it could be argued that their

combination, while richer, is also less precise. Clearly, there is

value in identifying the unique influences of the specific compo-

nents of virtuality that we combined. Examining the effects of each

component as a distinct moderator, in combination with the other

components, however, will necessitate sampling that can achieve

wide variance on each component and substantial sample sizes to

allow robust evaluations. These sampling issues would be com-

pounded as additional components of virtuality are proposed. This

is desirable research extension, although we acknowledge that

such data will be challenging to acquire.

Finally, generalization of research findings is always limited by

the nature of the sample. Our teams were engaged in research and

development activities and drawn from a diverse set of firms in the

global automotive and automotive supplies industry. Clearly there

is a need to replicate the findings in teams that work in other

contexts, industries, and cultural settings.

Practical Implications and Future Research

There are three main practical implications. First, our data

suggest that the influence of hierarchical leadership is mitigated in

virtual teams, as it is less strongly related to team performance

when teams are more virtual in nature. This finding suggests that

providing virtual team leaders with appropriate support, orienta-

tion, and/or training could be potentially useful. They might also

need more time and resources for leading their virtual team com-

pared to leading their respective face-to-face team. Second, struc-

tural supports are more strongly related to team performance in

more virtual teams. Thus, structural supports have the potential to

be an effective management tool for augmenting hierarchical lead-

ership and can be recommended to aid leaders managing virtual

teams. Structural supports comprise fair and reliable reward sys-

tems, and transparent communication and information manage-

ment. Based on our findings, structural supports should be imple-

mented to augment hierarchical leaders in virtual teams. Third,

although expected, shared leadership contributed to team perfor-

mance regardless of the degree of virtuality. Therefore, shared

leadership can be recommended for the management of all teams

along the virtuality continuum.

Based on our findings, structural supports can be recommended

for managing virtual teams and shared leadership can be recom-

mended for managing teams in general. With regard to structural

supports, future research should determine the extent to which

leaders, or others in the organization, could influence perceptions

of structural supports among virtual team members. For example,

high structural supports might be less salient when there are

restrictions in technology or resources, when reward systems do

not reward team performance (or any performance!), or when there

are low levels of organizational support. Another direction for

future research is to more systematically investigate the boundary

conditions of structural supports, as well as moderating variables

that might influence the effectiveness of structural supports.

Shared team leadership enhanced team performance regardless

of virtuality. This was unexpected, as the literature has viewed this

supplement as more important under greater degrees of virtuality.

This study extends prior literature with regard to the conception of

shared leadership as a means to supplement team functions, as it

captures the extent to which team members can collectively en-

gage in cognitive, affective/motivational, and behavioral team

leadership behaviors (Kozlowski & Bell, 2003).

Because the influence of shared leadership on team performance

was not affected by degrees of virtuality, shared team leadership

appears to have the potential to be a potent leadership approach.

However, there is a lack of research focused on the antecedents of

shared team leadership (e.g., Carson et al., 2007;Hoch, in press).

This has implications for theoretical extension and practical appli-

cation: the question of how to facilitate the emergence of shared

leadership has not been addressed by prior research or this study

(e.g., Pearce & Conger, 2003). Future research needs to identify

antecedents, mediators, and moderators of shared team leadership,

such as the impact of self-leadership and self-management (Manz,

1986;Neck & Houghton, 2006), group potency, group self-

efficacy, and team cohesion (Bandura, 1997;Chen, Gully, & Eden,

2001;Guzzo & Shea, 1992) or team and task conditions on shared

team leadership effects.

Conclusion

The nature of global competition and continuing advances in

communication technologies means that virtual teams are an inte-

gral aspect of work structure worldwide. They challenge what we

know and need to know about leading and managing teams. We

hope that these findings help to advance additional research on the

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

399

LEADING VIRTUAL TEAMS

role of leadership, and leadership supplements, for enhancing team

performance across the range of team virtuality.

References

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and

interpreting interactions. Newbury Park, CA: Sage.

Allen, T. D., Eby, L. T., Poteet, M. L., Lentz, E., & Lima, L. (2004). Career

benefits associated with mentoring for proteges: A meta-analysis. Jour-

nal of Applied Psychology, 89, 127–136. doi:10.1037/0021-9010.89.1

.127

Arbuckle, J. L. (2003). AMOS 5.0. Chicago, IL: Smallwaters.

Avolio, B. J., & Bass, B. M. (2004). MLQ—Multifactor Leadership Ques-

tionnaire. Menlo Park, CA: Mind Garden.

Avolio, B. J., Jung, D. I., Murry, W., & Sivasbramaniam, N. (1996).

Building highly developed teams: Focusing on shared leadership pro-

cesses, efficacy, trust, and performance. In M. M. Beyerlein, S. Beyer-

lein, & D. A. Johnson (Eds.), Advances in interdisciplinary studies of

work teams: Team leadership (pp. 173–209). Greenwich, CT: JAI Press.

Avolio, B. J., & Kahai, S. S. (2003). Adding the “E” to e-leadership: How

it may impact your leadership. Organizational Dynamics, 31, 325–338.

doi:10.1016/S0090-2616(02)00133-X

Avolio, B. J., Kahai, S. S., & Dodge, G. E. (2000). E-leadership: Impli-

cations for theory, research, and practice. The Leadership Quarterly, 11,

615–668. doi:10.1016/S1048-9843(00)00062-X

Baltes, B. B., Dickson, M. W., Sherman, M. P., Bauer, C. C., & LaGanke,

J. S. (2002). Computer mediated communication and group decision

making: A meta-analysis. Organizational Behavior and Human Deci-

sion Processes, 87, 156–179. doi:10.1006/obhd.2001.2961

Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY:

Freeman.

Bass, B. M. (1985). Leadership and performance beyond expectations.

New York, NY: Free Press.

Bass, B. M. (1998). Transformational leadership: Industrial, military, and

educational impact. Hillsdale, NJ: Erlbaum.

Bell, B. S., & Kozlowski, S. W. J. (2002). A typology of virtual teams:

Implications for effective leadership. Group & Organization Manage-

ment, 27, 14–49. doi:10.1177/1059601102027001003

Bishop, J. W., Scott, K. D., & Burroughs, S. M. (2000). Support, commit-

ment, and employee outcomes in a team environment. Journal of Man-

agement, 26, 1113–1132. doi:10.1177/014920630002600603

Blickle, G., & Boujataoui, M. (2005). Mentoren, Karriere und Geschlecht:

Eine Feldstudie mit Führungskräften aus dem Personalbereich [Mentors,

career, and gender: A field study with supervisors from personnel

departments]. Zeitschrift für Arbeits- und Organisationspsychologie, 49,

1–11. doi:10.1026/0932-4089.49.1.1

Bliese, P. D. (2000). Within-group agreement, non-interdependence, and

reliability—Implications for data aggregation and analysis. In K. J. Klein

& S. W. J. Kozlowski (Eds.), Multilevel theory, research, and methods

in organizations: Foundations, extensions and new directions (pp. 349–

382). San Francisco, CA: Jossey-Bass.

Bowers, D. G., & Seashore, S. E. (1966). Predicting organizational effec-

tiveness with a four-factor theory of leadership. Administrative Science

Quarterly, 11, 238–263. doi:10.2307/2391247

Brown, M. E., & Gioia, D. A. (2002). Making things click: Distributive

leadership in an online division of an offline organization. The Leader-

ship Quarterly, 13, 397–419. doi:10.1016/S1048-9843(02)00123-6

Buehner, M. (2004). Einführung in die Test- und Fragebogenkonstruktion-

[Introduction into Test and Questionnaire-Construction]. Munich, Ger-

many: Pearson.

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. doi:10.2307/

20159921

Chan, D. (1998). Functional relations among constructs in the same content

domain at different levels of analysis: A typology of composition mod-

els. Journal of Applied Psychology, 83, 234–246. doi:10.1037/0021-

9010.83.2.234

Chao, G. T., Walz, P., & Gardner, P. D. (1992). Formal and informal

mentorships: A comparison on mentoring functions and contrast with

nonmentored counterparts. Personnel Psychology, 45, 619–636.

Chen, G., Gully, C. S., & Eden, D. (2001). Validation of a new general

self-efficacy scale. Organizational Research Methods, 4, 62–83. doi:

10.1177/109442810141004

Chen, G., Kirkman, B. L., Kim, K. H., Farh, C. I. C., & Tangirala, S.

(2010). When does cross-cultural motivation enhance expatriate effec-

tiveness? A multilevel investigation of the moderating roles of subsid-

iary support and cultural distance. Academy of Management Journal, 53,

1110–1130. doi:10.5465/AMJ.2010.54533217

Cheshin, A., Rafaeli, A., & Bos, N. (2011). Anger and happiness in virtual

teams: Emotional influences of text and behavior on others’ affect in the

absence of non-verbal cues. Organizational Behavior and Human De-

cision Processes, 116, 2–16. doi:10.1016/j.obhdp.2011.06.002

Chin, W. W. (2001). PLS-graph user’s guide: Version 3.0. Houston, TX:

University of Houston, C. T. Bauer College of Business.

Clampitt, P. G., & Downs, C. W. (2004). Down–Hazen Communication

Satisfaction Questionnaire. In C. W. Downs & A. D. Adrian (Eds.),

Assessing organizational communication (pp. 139–157). New York,

NY: Guilford Press.

Colquitt, J. A. (2004). Does the justice of the one interact with the justice

of the many? Reactions to procedural justice in teams. Journal of

Applied Psychology, 89, 633–646. doi:10.1037/0021-9010.89.4.633

Day, D. V., Gronn, P., & Salas, E. (2004). Leadership capacity in teams.

The Leadership Quarterly, 15, 857–880. doi:10.1016/j.leaqua.2004.09

.001

Duarte, D. L., & Snyder, N. T. (2001). Mastering virtual teams (2nd ed.).

San Francisco, CA: Jossey-Bass.

Dulebohn, J. H., & Martocchio, J. J. (1998). Employee perceptions of the

fairness of work group incentive plans. Journal of Management, 24,

469–488.

Edmondson, A. (1999). Psychological safety and learning behavior in work

teams. Administrative Science Quarterly, 44, 350–383. doi:10.2307/

2666999

Edmondson, A., Bohmer, R. M., & Pisano, G. P. (2001). Disrupted

routines: Team learning and new technology implementation in hospi-

tals. Administrative Science Quarterly, 46, 685–716. doi:10.2307/

3094828

Efron, B., & Tibshirani, R. J. (1993). An introduction to the bootstrap. New

York, NY: Chapman & Hall/CRC.

Eisenberger, R., Huntington, R., Hutchison, S., & Sowa, D. (1986). Per-

ceived organizational support. Journal of Applied Psychology, 71, 500–

507. doi:10.1037/0021-9010.71.3.500

Ensley, M. D., Hmieleski, K. M., & Pearce, C. L. (2006). The importance

of vertical and shared leadership within new venture top management

teams: Implications for the performance of startups. The Leadership

Quarterly, 17, 217–231. doi:10.1016/j.leaqua.2006.02.002

Faraj, S., & Sproull, L. (2000). Coordinating expertise in software devel-

opment teams. Management Science, 46, 1554–1568. doi:10.1287/mnsc

.46.12.1554.12072

Fiol, C. M., & O’Connor, E. J. (2005). Identification in face-to-face,

hybrid, and pure virtual teams: Untangling the contradictions. Organi-

zation Science, 16, 19–32. doi:10.1287/orsc.1040.0101

Fleishman, E. A., Mumford, M. D., Zaccaro, S. J., Levin, K. Y., Korotkin,

A. L., & Hein, M. B. (1991). Taxonomic efforts in the description of

leader behavior: A synthesis and functional interpretation. The Leader-

ship Quarterly, 2, 245–287. doi:10.1016/1048-9843(91)90016-U

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

400 HOCH AND KOZLOWSKI

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models

with unobservable variables and measurement error. Journal of Market-

ing Research, 18, 39–50. doi:10.2307/3151312

Fuller, J. B., Patterson, C. E. P., Hester, K., & Stringer, D. Y. (1996). A

quantitative review of research on charismatic leadership. Psychological

Reports, 78, 271–287. doi:10.2466/pr0.1996.78.1.271

Gemuenden, H. G., & Hoegl, M. (2001). Management von Teams: Theo-

retische Konzepte und empirische Befunde [Management of teams, the-

oretical concepts, and empirical results]. Wiesbaden, Germany: Gabler.

Gerstner, C. R., & Day, D. V. (1997). Meta-analytic review of leader–

member exchange theory: Correlates and construct issues. Journal of

Applied Psychology, 82, 827–844. doi:10.1037/0021-9010.82.6.827

Gibson, C. B., & Cohen, S. G. (2003). Virtual teams that work: Creating

conditions for virtual team effectiveness. San Francisco, CA: Jossey-

Bass.

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.

Graen, G. B. (1976). Role-making processes within complex organizations.

In M. D. Donette (Ed.), Handbook of industrial and organizational

psychology (pp. 1201–1245). Chicago, IL: Rand-McNally.

Graen, G., Novak, M., & Sommerkamp, P. (1982). The effects of leader–

member exchange and job design on productivity and satisfaction:

Testing a dual attachment model. Organizational Behavior and Human

Performance, 30, 109–131. doi:10.1016/0030-5073(82)90236-7

Graen, G., & Uhl-Bien, M. (1995). Relationship-based approach to lead-

ership: Development of leader–member exchange (LMX) theory of

leadership over 25 years: Applying a multi-level multi-domain perspec-

tive. The Leadership Quarterly, 6, 219–247. doi:10.1016/1048-

9843(95)90036-5

Griffith, T. L., Sawyer, J. E., & Neale, M. A. (2003). Virtualness and

knowledge in teams: Managing the love triangle of organizations, indi-

viduals, and information technology. MIS Quarterly, 27, 265–287.

Guzzo, R. A., & Shea, G. P. (1992). Group performance and intergroup

relations in organizations. Palo Alto, CA: Consulting Psychologists

Press.

Hambley, L. A., O’Neill, T. A., & Kline, T. J. B. (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

Hamilton, B. A., & Scandura, T. A. (2003). E-mentoring: Implications for

organizational learning and development in a wired world. Organiza-

tional Dynamics, 31, 388–402. doi:10.1016/S0090-2616(02)00128-6

Hill, S. N., Bartol, K. M., Tesluk, P. E., & Langa, G. A. (2009). Organi-

zational context and face-to-face interaction: Influences on the develop-

ment of trust and collaborative behaviors in computer-mediated groups.

Organizational Behavior and Human Decision Processes, 108, 187–

201. doi:10.1016/j.obhdp.2008.10.002

Hinds, P., & Kiesler, S. (2002). Distributed work. Cambridge, MA: MIT

Press.

Hinds, P., Liu, L., & Lyon, J. (2011). Putting the global in global work: An

intercultural lens on the practice of cross-national collaboration. The

Academy of Management Annals, 5, 135–188. doi:10.1080/19416520

.2011.586108

Hoch, J. E. (in press). Shared leadership and innovation: The role of

vertical leadership and employee integrity. Journal of Business and

Psychology.

Hoegl, M., & Gemuenden, H. G. (2001). Teamwork quality and the success

of innovative projects: A theoretical concept and empirical evidence.

Organization Science, 12, 435–449. doi:10.1287/orsc.12.4.435.10635

Hofmann, D. A., & Stetzer, A. (1996). A cross-level investigation of

factors influencing unsafe behaviors and accidents. Personnel Psychol-

ogy, 49, 307–339. doi:10.1111/j.1744-6570.1996.tb01802.x

Hollingshead, A. B., & McGrath, J. E. (1995). Computer-assisted groups:

A critical review of the empirical research. In R. A. Guzzo & E. Salas

(Eds.), Team effectiveness and decision making in organizations (pp.

46–78). San Francisco, CA: Jossey-Bass.

Howell, J. M., & Hall-Merenda, K. (1999). The ties that bind: The impact

of leader–member exchange, transformational and transactional leader-

ship, and distance on predicting follower performance. Journal of Ap-

plied Psychology, 84, 680–694. doi:10.1037/0021-9010.84.5.680

Howell, J. M., Neufeld, D. J., & Avolio, B. J. (2005). Examining the

relationship of leadership and physical distance with business unit per-

formance. The Leadership Quarterly, 16, 273–285. doi:10.1016/j.leaqua

.2005.01.004

Howell, J. P., & Dorfman, P. W. (1981). Substitutes for leadership: Test of

a construct. Academy of Management Journal, 24, 714–728. doi:

10.2307/256171

Howell, J. P., & Dorfman, P. W. (1986). Leadership and substitutes for

leadership among professional and non-professional workers. Jour-

nal of Applied Behavioral Science, 22, 29–46. doi:10.1177/

002188638602200106

i4cp. (2006, May 5). Beyond virtual teams. Retrieved from http://www

.i4cp.com/trendwatchers/2006/05/05/beyond-virtual-teams

i4cp. (2008, September 4). Virtual teams now a reality: Two out of three

companies say they will rely more on virtual teams in the future.

Retrieved from http://www.i4cp.com/news/2008/09/04/virtual-

teams-now-a-reality

Irwin, J. R., & McClelland, G. H. (2003). Negative consequences of

dichotomizing continuous predictor variables. Journal of Market Re-

search, 40, 366–371. doi:10.1509/jmkr.40.3.366.19237

Jarvenpaa, S. L. (2004). Toward conceptualized theories of trust: The role

of trust in global virtual teams. Information Systems Research, 15,

250–267. doi:10.1287/isre.1040.0028

Jarvenpaa, S. L., & Leidner, D. E. (1999). Communication and trust in

global virtual teams. Organization Science, 10, 791–815. doi:10.1287/

orsc.10.6.791

Judge, T. A., & Piccolo, R. F. (2004). Transformational and transactional

leadership: A meta-analytic test of their relative validity. Journal of

Applied Psychology, 89, 755–768. doi:10.1037/0021-9010.89.5.755

Jung, D. I., & Sosik, J. J. (2002). Transformational leadership in work

groups: The role of empowerment, cohesiveness, and collective-efficacy

on perceived group performance. Small Group Research, 33, 313–336.

doi:10.1177/10496402033003002

Kacmar, K. M., Witt, L. A., Zivnuska, S., & Gully, S. M. (2003). The

interactive effect of leader–member exchange and communication fre-

quency on performance ratings. Journal of Applied Psychology, 88,

764–772. doi:10.1037/0021-9010.88.4.764

Kahai, S. S., Sosik, J. J., & Avolio, B. J. (2003). Effects of leadership style,

anonymity, and rewards on creativity-relevant processes and outcomes

in an electronic meeting system context. The Leadership Quarterly, 14,

499–524. doi:10.1016/S1048-9843(03)00049-3

Kanawattanachai, P., & Yoo, Y. (2007). The impact of knowledge coor-

dination on virtual team performance over time. MIS Quarterly, 31,

783–808.

Kasper-Fuehrer, E. C., & Ashkanasy, N. M. (2001). Communicating trust-

worthiness and building trust in inter-organizational virtual organiza-

tions. Journal of Management, 27, 235–254.

Kerr, S. (1977). Substitutes for leadership: Some implications for organi-

zational design. Organization and Administrative Sciences, 8, 135–146.

Kerr, S., & Jermier, J. M. (1978). Substitutes for leadership: Their meaning

and measurement. Organizational Behavior and Human Performance,

22, 375–403. doi:10.1016/0030-5073(78)90023-5

Kiesler, S., & Cummings, J. N. (2002). What do we know about proximity

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

401

LEADING VIRTUAL TEAMS

and distance in work groups? A legacy of research.In P. Hinds & S.

Kiesler (Eds.), Distributed work (pp. 57–80). Cambridge, MA: MIT

Press.

Kirkman, B. L., Gibson, C. B., & Kim, K. (2012). Across borders and

technologies: Advancements in virtual teams research. In S. W. J.

Kozlowski (Ed.), Oxford handbook of organizational psychology (Vol.

2, pp. 789–858). New York, NY: Oxford University Press.

Kirkman, B. L., & Malthieu, J. E. (2005). The dimensions and antecedents

of team virtuality. Journal of Management, 31, 700–718. doi:10.1177/

0149206305279113

Kirkman, B. L., Rosen, B., Tesluk, P. E., & Gibson, C. B. (2004). The

impact of team empowerment on virtual team performance: The mod-

erating role of face-to-face-interaction. Academy of Management Jour-

nal, 47, 175–192. doi:10.2307/20159571

Klein, K. J., Bliese, P. D., Kozolowski, S. W. J., Dansereau, F., Gavin,

M. B., Griffin, M. A.,...Bligh, M. C. (2000). Multilevel analytical

techniques: Commonalities, differences, and continuing questions. In

K. J. Klein & S. W. J. Kozlowski (Eds.), Multilevel theory, research, and

methods in organizations: Foundations, extensions, and new directions

(pp. 512–553). San Francisco, CA: Jossey-Bass.

Kozlowski, S. W. J., & Bell, B. S. (2003). Work groups and teams in

organizations. In W. C. Borman, D. R. Ilgen, & R. J. Klimoski (Eds.),

Comprehensive handbook of psychology: Industrial and organizational

psychology (pp. 333–375). New York, NY: Wiley.

Kozlowski, S. W. J., & Ilgen, D. R. (2006). Enhancing the effectiveness of

work groups and teams. Psychological Science in the Public Interest, 7,

77–124.

Kozlowski, S. W. J., & Klein, K. J. (2000). A multilevel approach to theory

and research in organizations: Contextual, temporal, and emergent pro-

cesses. In K. J. Klein & S. J. Kozlowski (Eds.), Multilevel theory,

research, and methods in organizations: Foundations, extensions, and

new directions (pp. 3–90). San Francisco, CA: Jossey-Bass.

Kram, K. E. (1985). Mentoring at work. Glenview, IL: Scott Foresman and

Company.

Künzle, B., Zala-Mezö, E., Wacker, J., Kolbe, M., Spahn, D. R., & Grote,

G. (2010). Leadership in anaesthesia teams: The most effective leader-

ship is shared. Quality and Safety Health Care, 19, 1–6. doi:10.1136/

qshc.2008.030262

Lipnack, J., & Stamps, J. (2000). Virtual teams: People working across

boundaries with technology. New York, NY: Wiley.

Lowe, K. B., Kroeck, K. G., & Sivasubramaniam, N. (1996). Effectiveness

correlates of transformational leadership and transactional leadership: A

meta-analytic review of the MLQ literature. The Leadership Quarterly,

7, 385–425. doi:10.1016/S1048-9843(96)90027-2

MacCallum, R. C., Zhang, S., Preacher, K. J., & Rucker, D. D. (2002). On

the practice of dichotomization of quantitative variables. Psychological

Methods, 7, 19–40. doi:10.1037/1082-989X.7.1.19

Majchrzak, A., Malhotra, A., Stamps, J., & Lipnack, J. (2004, May). Can

absence make a team grow stronger? Harvard Business Review, 1–9.

Malhotra, A., & Majchrzak, A. (2004). Enabling knowledge creation in

far-flung teams: Best practices for IT support and knowledge sharing.

Journal of Knowledge Management, 8, 75–88. doi:10.1108/

13673270410548496

Malhotra, A., Majchrzak, A., & Rosen, B. (2007). Leading virtual teams.

The Academy of Management Perspectives, 21, 60–70. doi:10.5465/

AMP.2007.24286164

Manz, C. C. (1986). Self-leadership: Toward an expanded theory of self-

influence processes in organizations. The Academy of Management

Review, 11, 585–600.

Martins, L. L., Gilson, L. L., & Maynard, M. T. (2004). Virtual teams:

What do we know and where do we go from here? Journal of Manage-

ment, 30, 805–835. doi:10.1016/j.jm.2004.05.002

Martins, L. L., & Shalley, C. E. (2011). Creativity in virtual work: Effects

of demographic differences. Small Group Research, 42, 536–561. doi:

10.1177/1046496410397382

Mayo, M., Meindl, J. R., & Pastor, J. C. (2003). Shared leadership in work

teams. In C. L. Pearce & J. A. Conger (Eds.), Shared leadership:

Reframing the hows and whys of leadership (pp. 193–214). doi:10.4135/

9781452229539.n9

McGrath, J. E. (1962). Leadership behavior: Some requirements for lead-

ership training. Washington, DC: U.S. Civil Service Commission, Of-

fice of Career Development.

Mehra, A., Smith, B. R., Dixon, A. L., & Robertson, B. (2006). Distributed

leadership in teams: The network of leadership perceptions and team

performance. The Leadership Quarterly, 17, 232–245. doi:10.1016/j

.leaqua.2006.02.003

Mesmer-Magnus, J. R., DeChurch, L. A., Jimenez-Rodriguez, M., Wild-

man, J., & Shuffler, M. (2011). A meta-analytic investigation of virtu-

ality and information sharing in teams. Organizational Behavior and

Human Decision Processes, 115, 214–225. doi:10.1016/j.obhdp.2011

.03.002

Morgeson, F. P., DeRue, D. S., & Karam, E. P. (2010). Leadership in

teams: A functional approach to understanding leadership structures and

processes. Journal of Management, 36, 5–39. doi:10.1177/

0149206309347376

Neck, C. P., & Houghton, J. D. (2006). Two decades of self-leadership

theory and research. Journal of Managerial Psychology, 21, 270–295.

doi:10.1108/02683940610663097

Noe, R. A. (1988). An investigation of the determinants of successful

assigned mentoring relationships. Personnel Psychology, 41, 457–479.

doi:10.1111/j.1744-6570.1988.tb00638.x

O’Leary, M. B., & Cummings, J. N. (2007). The spatial, temporal, and

configurational characteristics of geographic dispersion in teams. MIS

Quarterly, 31, 433–452.

O’Leary, M. B., & Mortensen, M. (2010). Go con(figure): Subgroups,

imbalance, and isolates in geographically dispersed teams. Organization

Science, 21, 115–131. doi:10.1287/orsc.1090.0434

Ostroff, C., & Kozlowski, S. W. J. (1993). The role of mentoring in the

information gathering processes of newcomers during early organiza-

tional socialization. Journal of Vocational Behavior, 42, 170–183. doi:

10.1006/jvbe.1993.1012

Pearce, C. L. (2004). The future of leadership: Combining vertical and

shared leadership to transform knowledge work. Academy of Manage-

ment Executive, 18, 47–57. doi:10.5465/AME.2004.12690298

Pearce, C. L., & Conger, J. A. (2003). Shared leadership: Reframing the

hows and whys of leadership. Thousand Oaks, CA: Sage.

Pearce, C. L., & Manz, C. C. (2005). The new silver bullets of leadership:

The importance of self and shared leadership in knowledge work.

Organizational Dynamics, 34, 130–140. doi:10.1016/j.orgdyn.2005.03

.003

Pearce, C. L., & Sims, H. P., Jr. (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

Pearce, C. L., Yoo, Y., & Alavi, M. (2004). Leadership, social work and

virtual teams: The relative influence of vertical versus shared leadership

in the nonprofit sector. In R. E. Riggio, S. Smith-Orr, & J. Shakely

(Eds.), Improving leadership in nonprofit organizations (pp. 180–203).

San Francisco, CA: Jossey-Bass.

Peters, L., & Karren, R. J. (2009). An examination of the roles of trust and

functional diversity on virtual team performance ratings. Group &

Organization Management, 34, 479–504. doi:10.1177/

1059601107312170

Podsakoff, P. M., & MacKenzie, S. B. (1994). An examination of the

psychometric properties and nomological validity of some revised and

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

402 HOCH AND KOZLOWSKI

reduced “substitutes for leadership” scales. Journal of Applied Psychol-

ogy, 79, 702–713. doi:10.1037/0021-9010.79.5.702

Podsakoff, P. M., MacKenzie, S. B., & Bommer, W. H. (1996). Meta-

analysis of the relationships between Kerr and Jermier’s substitutes for

leadership and employee job attitudes, role perceptions, and perfor-

mance. Journal of Applied Psychology, 81, 380–399. doi:10.1037/0021-

9010.81.4.380

Purvanova, R. K., & Bono, J. E. (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

Riley, S., & Wrench, D. (1985). Mentoring among women lawyers. Jour-

nal of Applied Social Psychology, 15, 374–386. doi:10.1111/j.1559-

1816.1985.tb00913.x

Ringle, C. M., Wende, S., & Will, A. (2006). SmartPLS (Version 2.0 M3).

Retrieved from http://www.smartpls.de

Sambamurthy, V., & Chin, W. W. (1994). The effects of group attitudes

toward alternative GDSS designs on the decision-making performance

of computer-supported groups. Decision Sciences, 25, 215–241. doi:

10.1111/j.1540-5915.1994.tb01840.x

Sarker, S., Anjuja, M., Sarker, S., & Kirkeby, S. (2011). The role of

communication and trust in global virtual teams: A social network

perspective. Journal of Management Information Systems, 28, 273–309.

doi:10.2753/MIS0742-1222280109

Scandura, T. A., & Ragins, B. R. (1993). The effects of sex and gender role

orientation on mentorship in male-dominated occupations. Journal of

Vocational Behavior, 43, 251–265. doi:10.1006/jvbe.1993.1046

Schminke, M., Cropanzano, R., & Rupp, D. E. (2002). Organization

structure and fairness perceptions: The moderating effects of organiza-

tional level. Organizational Behavior and Human Decision Processes,

89, 881–905. doi:10.1016/S0749-5978(02)00034-1

Seers, A. (1989). Team-member exchange quality: A new construct for

role-making research. Organizational Behavior and Human Decision

Processes, 43, 118–135.

Sherony, K. M., & Green, S. G. (2002). Coworker exchange: Relationships

between coworkers, leader–member exchange, and work attitudes. Jour-

nal of Applied Psychology, 87, 542–548. doi:10.1037/0021-9010.87.3

.542

Shin, Y. (2004). A person–environment fit model for virtual organizations.

Journal of Management, 30, 725–743. doi:10.1016/j.jm.2004.03.002

Siebdraht, F., Hoegl, M., & Ernst, H. (2009). How to manage virtual teams.

MIT Sloan Management Review, 50, 63–69.

Sosik, J. J., Avolio, B. J., & Kahai, S. S. (1997). Effects of leadership style

and anonymity on group potency and effectiveness in a group decision

support system environment. Journal of Applied Psychology, 82, 89–

103. doi:10.1037/0021-9010.82.1.89

Stanko, T. L., & Gibson, C. B. (2009). The role of cultural elements in

virtual teams. In R. S. Bhagat & R. M. Steers (Eds.), Cambridge

handbook of culture, organization, and work (pp. 272–304). doi:

10.1017/CBO9780511581151.012

Staples, D., & Zhao, L. (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

Townsend, A. M., DeMarie, S. M., & Hendrickson, A. R. (1998). Virtual

teams: Technology and the workplace of the future. Academy of Man-

agement Executive, 12, 17–29.

Tsui, A. S., Nifadkar, S. S., & Ou, A. Y. (2007). Cross-national, cross-

cultural organizational behavior research, advances, gaps, and recom-

mendations. Journal of Management, 33, 426–478. doi:10.1177/

0149206307300818

Tyran, K. L., Tyran, C. G., & Shepherd, M. (2003). Exploring emerging

leadership in virtual teams. In C. B. Gibson & S. G. Cohen (Eds.),

Virtual teams that work: Creating conditions for virtual team effective-

ness (pp. 183–195). San Francisco, CA: Jossey-Bass.

Van Der Vegt, G. S., Emans, B., & Van De Vliert, E. (2000). Team

members’ affective responses to patterns of intragroup interdependence

and job complexity. Journal of Management, 26, 633–655.

Wayne, S. J., Shore, L. M., & Liden, R. C. (1997). Perceived organiza-

tional support and leader–member exchange: A social exchange per-

spective. Academy of Management Journal, 40, 82–111. doi:10.2307/

257021

Whitely, W. T., Dougherty, T. W., & Dreher, G. F. (1991). Relationship of

career mentoring and socioeconomic origin to managers’ and profes-

sionals’ early career progress. Academy of Management Journal, 34,

331–350. doi:10.2307/256445

Wiesenfeld, B. M., Raghuram, S., & Garud, R. (1999). Communication

patterns as determinants of organizational identification in a virtual

organization. Organization Science, 10, 777–790. doi:10.1287/orsc.10.6

.777

Wunderer, R. (2002). Fuehrung und Zusammenarbeit: Einer unternehmer-

ische Fuehrungslehre [Leadership and collaboration: Organizational

leadership instruction] (4th ed.). Neuwied, Germany: Kriftel.

Yukl, G. (2010). Leadership in organizations (7th ed.). Englewood Cliffs,

NJ: Prentice-Hall.

Zaccaro, S. J., & Bader, P. (2003). E-leadership and the challenges of

leading e-teams: Minimizing the bad and maximizing the good. Orga-

nizational Dynamics, 31, 377–387. doi:10.1016/S0090-

2616(02)00129-8

Zaccaro, S. J., Rittman, A. L., & Marks, M. A. (2001). Team leadership.

The Leadership Quarterly, 12, 451–483. doi:10.1016/S1048-

9843(01)00093-5

Zigurs, I. (2003). Leadership in virtual teams: Oxymoron or opportunity?

Organizational Dynamics, 31, 339–351. doi:10.1016/S0090-

2616(02)00132-8

Received August 27, 2011

Revision received July 9, 2012

Accepted July 18, 2012 䡲

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

403

LEADING VIRTUAL TEAMS

A preview of this full-text is provided by American Psychological Association.

Learn more

Content available from Journal of Applied Psychology

This content is subject to copyright. Terms and conditions apply.

Uncertainty-media fit and Psychological Capital for Trust Building in Virtual Leader-Follower Interactions

Article

Jan 2025
J Leader Organ Stud

A very important challenge facing leaders and followers alike is how to navigate the virtual workplace where much of our communication and interactions occur through the use of technology. This field experiment examined whether a leader's choice of communication media given the situational uncertainty (termed uncertainty-media fit here to parallel related research) impacted the amount and type of trust (cognitive versus affective) that developed between leaders and followers. Further, we tested whether the leader's perceived level of psychological capital (PsyCap) impacted the results obtained. To test our hypotheses, 326 participants were randomly assigned to one of four conditions of high (low) media richness×high (low) situational uncertainty. Results of our study indicated that communication media choice, in and of itself, did not seem to impact results. However, the situational uncertainty present in our scenarios impacted subjects’ amount and type of trust in the leaders, lending credence to the argument that perhaps technology is, in fact, more based on how it is interpreted, rather than whether the leader uses media higher in richness to communicate more complex information. Further, subjects’ perception of the leader's psychological capital (PsyCap) moderated results obtained. In addition to limitations and suggestions for future research, we conclude with practical implications for leaders that may have an impact on the amount and type of trust that develops between leaders and followers in a virtual work environment.

Navigating Virtual Frontiers: The Willingness of Virtual Teams to Use the Metaverse

Conference Paper

Jun 2024

The metaverse offers an environment for immersive collaboration for the constantly growing number of virtual teams (VTs). However, there still needs to be a greater understanding of the willingness to use the metaverse from the perspective of VT leaders and their subordinated VT members. Against this background, we conducted a quantitative study (N=249) comparing these perspectives. We found significant differences between both groups by adapting the extended Unified Theory of Acceptance and Use of Technology (UTAUT) to the research context. The key findings indicate that social presence is critically important, particularly for VT leaders, and it even surpasses performance expectations in significance. Moreover, the study highlights the importance of privacy concerns, which are notably significant for VT members but not for VT leaders. Thus, our research offers new insights for research, and organisations can boost users’ willingness to use the metaverse.

Generational diversity and team innovation: the roles of conflict and shared leadership

Article

Full-text available

Jan 2025

The increasing generational diversity in modern teams has sparked an ongoing debate about its impact on team performance. Grounded in decision-making and social identity theories, this study explores the multifaceted relationship between generational diversity and team innovation performance, examining the mediating roles of cognitive and affective conflicts and the moderating role of shared leadership. The findings from a three-wave survey of five multi-generational teams in a Chinese organization reveal that generational diversity predicts both cognitive and affective conflicts, which subsequently exert opposing effects on team innovation. Shared leadership positively moderates the relationship between cognitive conflict and team innovation, amplifying the indirect positive effect of generational diversity. However, shared leadership does not moderate the relationship between affective conflict and team innovation. These results offer a more nuanced understanding of the dual role of generational diversity in team innovation and underscore the importance of shared leadership in harnessing its potential benefits.

The Impact of Leadership and Management Changes on the Military Organization

Article

Full-text available

Dec 2024

Leadership in a military organization is a multi-faceted phenomenon that involves expanding vision, enhancing performance, and cultivating personality beyond conventional boundaries. Effective military leaders not only inspire and guide their people, but also articulate a clear and compelling vision of future tasks and goals. Military leaders perform key tasks such as setting and explaining strategic goals, assessing the feasibility of long-term operational plans, and ensuring the adequacy of organizational structures to achieve those goals. The issue of leadership in the military organization is of paramount importance, as the stakes in military operations are high and the cohesion of well-motivated units capable of executing complex missions under pressure is critical. Effective leadership is essential for maintaining discipline, morale and operational effectiveness in the face of adversity. This article addresses the essential qualities and responsibilities of leadership in a military context, emphasizing the importance of vision in motivating and leading personnel. It examines how military leaders can effectively communicate their vision and values to create a guiding fire that inspires their units to greater success and performance. Through a comprehensive analysis of leadership behaviors and the impact of vision orientation, the article provides insights into the mechanisms by which military leaders can enhance performance and foster a culture of excellence and readiness.

Enhancing organizational commitment through shared leadership: insights from Saudi higher education

Article

Full-text available

Nov 2024

Atiyah A. Alghamdi

This study investigates the impact of shared leadership (SL) on the various dimensions of organizational commitment (OC) within Saudi higher education institutions (HEIs). Employing a descriptive cross-sectional survey design, data were collected from faculty members at a prominent Saudi university using structured questionnaires. The questionnaires included validated scales for SL, encompassing dimensions such as Development and Mentoring, Problem-Solving, Support and Consideration, and Planning and Organizing, as well as for OC, which measured affective, normative, and continuance commitment. Descriptive statistics, correlation, and regression analyses were used to assess the relationships between SL and OC components. The findings indicate that shared leadership is widely practiced, with Development and Mentoring emerging as the most prominent SL dimension. A significant positive relationship was identified between SL and all three OC components, with affective commitment demonstrating the strongest correlation. Additionally, SL was found to significantly predict overall OC, underscoring its role in enhancing faculty commitment. These results highlight the potential of adopting shared leadership practices in HEIs to strengthen faculty engagement and institutional performance. Future research should expand data collection across multiple institutions and examine the combined influence of SL and OC on the quality of education and institutional success.

Task interdependence and shared leadership: A structural perspective on the distribution of leadership in teams

Article

Jan 2025

Shared leadership has consistently been shown to predict team effectiveness. However, research also indicates that different teams may require different configurations of shared leadership, and achieving maximum sharedness in leadership does not always guarantee superior team outcomes. This reality underscores the need for a normative theory of shared leadership that can extend our understanding of the construct and facilitate its adoption in organizations. Despite the significance of such a theory, little attention has been given to its development and our understanding of how shared leadership should be distributed across different teams remains quite limited. In this article, we adopt a structural perspective to propose that the task interdependence network can serve as a robust foundation for devising effective shared leadership strategies. Our conceptual framework outlines the nuanced implications of the task interdependence network—from determining the optimal level of shared leadership necessary for performance to identifying potential members for shared leadership responsibilities. In doing so, we emphasize that the specific implications of the task interdependence network may vary, rather than remain uniform, across different dimensions of shared leadership.

Performans Yönetimi ve Geri Bildirim

Chapter

Full-text available

Oct 2024

Tolga Anıl Topdemir

Advancing Quality and Safety Culture in Healthcare: Insights From the Evaluation of an Improvement Science Program for Nurses and Midwives

Article

Full-text available

Jan 2025
J ADV NURS

Aims This paper presents the outcomes and insights gained from the implementation of an Improvement Science program tailored for nursing and midwifery staff within a large local health district in New South Wales. The programme aimed to enhance frontline clinicians' confidence and capability in quality improvement, ultimately improving patient outcomes and safety culture. Design Through an explanatory sequential mixed‐methods evaluation study, we assessed the programme's effectiveness in building capacity, sustaining practice changes and fostering a culture of continuous improvement. Methods Quantitative data were collected through pre‐post knowledge surveys, post workshop feedback and programme participation rates. Qualitative data were then collected via nine interviews with programme participants. Simple descriptive statistical analysis for quantitative data and a thematic analysis of qualitative data was undertaken. Data were then integrated from these multiple sources to gain a deeper understanding of the outcomes of the Improvement Science Program. Results Key findings indicate that coaching and mentoring support significantly contributed to project completion and sustained practice changes. Structured coaching sessions, collaborative team meetings, and executive sponsorship were vital components that facilitated successful outcomes. Notably, effective leadership, often demonstrated by Clinical Nurse Educators and Consultants, played a crucial role in fostering staff collaboration and participation. Insights from qualitative interviews highlight the transformative impact of the programme on participants' skills, confidence and practice. Conclusion The paper concludes with recommendations for future Improvement Science programs, emphasising the importance of structured coaching, accountability mechanisms, and the identification and support of future coaches. Overall, this study underscores the value of ongoing training initiatives in promoting a culture of safety, quality improvement and enhanced patient outcomes in healthcare settings. Patient or Public Contribution This study had no patient or public contribution. Reporting Method Adherence to Standards for Reporting Qualitative Research (SRQR) EQUATOR guidelines (see Supplementary file).

Steering New Normal: School Administrators’ Lived Experiences of Educational Innovations Amidst COVID-19 Pandemic

Article

Dec 2024

Using genre analysis for conceptualising virtual team collaborations with complex role and work context connections: what implementation problems can occur?

Article

Nov 2024
BEHAV INFORM TECHNOL

Coworker Exchange: Relationships Between Coworkers, Leader-Member Exchange, and Work Attitudes

Article

Full-text available

Jun 2002

The study of leadership exchanges is extended by studying both leader-member exchanges (LMXs) and coworker exchanges (CWXs). Data from 110 coworker dyads were used to examine relationships between LMXs and CWXs and between exchange relationships and work attitudes. As predicted, the interaction between 2 coworkers' LMX scores predicted CWX quality for the coworker dyad. Also, after controlling for LMX, greater diversity in a worker's CWX relationships was negatively related to his or her organizational commitment but not job satisfaction. The quality of a worker's CWX relationships, however, did not moderate the relationship between CWX diversity and work attitudes.

Support, Commitment, and Employee Outcomes in a Team Environment

Article

Full-text available

Nov 2000
J MANAGE

This field study investigated whether perceived team support and team commitment relate to employee outcomes differently than perceived organizational support and organizational commitment. A LISREL analysis was conducted on data from 380 manufacturing plant employees and 9 supervisors. Job performance was related to team commitment; intention to quit was related to organizational commitment ; and organizational citizenship behavior was related to both team and organizational commitment. Commitment mediated the relationships between support and the outcome variables.

Shared Leadership: Reframing the Hows and Whys of Leadership

Book

Jan 2003

Shared Leadership: Reframing the Hows and Whys of Leadership brings together the foremost thinkers on the subject and is the first book of its kind to address the conceptual, methodological, and practical issues for shared leadership. Its aim is to advance understanding along many dimensions of the shared leadership phenomenon: its dynamics, moderators, appropriate settings, facilitating factors, contingencies, measurement, practice implications, and directions for the future. The volume provides a realistic and practical discussion of the benefits, as well as the risks and problems, associated with shared leadership. It will serve as an indispensable guide for researchers and practicing managers in identifying where and when shared leadership may be appropriate for organizations and teams.

Self-efficacy: the exercise of control

Book

Jan 1997

A. Bandura

The effects of group attitudes toward alternative GDSS designs on the decision-making performance of computer-supported groups

Article

Jan 1994

Computer-Assisted Groups: A Critical Review of the Empirical Research

Article

Jan 1995

No Abstract

The role of cultural elements in virtual teams

Article

Jan 2009

Work groups and teams in organizations

Article

Jan 2013

Multilevel analytical techniques: Commonalities, differences, and continuing questions

Article

Jan 2000

Group performance and intergroup relations in organizations

Article

Jan 1992

Leading Virtual Teams: Hierarchical Leadership, Structural Supports, and Shared Team Leadership

Abstract

Recommended publications

Is the Most Effective Team Leadership Shared?: The Impact of Shared Leadership, Age Diversity, and C...

Team personality composition, emergent leadership and shared leadership in virtual teams: A theoreti...

Shared Leadership in Virtual Teams: Contingencies of Collective Team Leadership in Virtual Teams

Shared Leadership and Innovation: The Role of Vertical Leadership and Employee Integrity

Socio-demographic factors and shared leadership behaviors in dispersed teams: Implications for human...