A Typology Framework for Virtual Teams

img WHITE PAPER

2016

Ann Ledwith (PhD, MBA, CEng), Padhraic Ludden (Ind. Eng., MPM, PMP)

Enterprise Research Centre, University of Limerick
Limerick, Ireland

Table of Contents

Acknowledgments

Executive Summary

Introduction

Background

Temporal

Geographic

Cultural

Social

Political

Team Membership

Communication Technology

Task Complexity

Team Virtuality

Methodology

Development of Research Instrument

Virtuality Measure

Data Analysis

Results

Demographic Results

Empirically Based Virtual Team Typologies

Virtually Enhanced and Virtually Challenged Typologies

Highly Virtual and Moderately Virtual Typologies

Virtually Challenged Versus Virtually Enhanced Team Comparisons

Face-to-Face Meeting That Involved Team Members

The Cost of the Project

Knowledge Diversity of the Team Members

Temporal Dispersion Factors for Virtually Challenged and Enhanced Typologies

Communication Technology Usage and Task Complexity Factors for Virtually Challenged and Enhanced Typologies

Highly Virtual Versus Moderately Virtual Team Comparisons

Face-to-Face Meeting That Involved all Team Members

All Team Members Were of the Same Nationality

Official Mandatory Language for the Team

Existence of a Main Location

The Makeup of Team Members at Locations

The Cost of the Project

Size of the Organization Executing the Project

Classification of the Project Organization

Temporal Dispersion Factors for Highly Virtual and Moderately Virtual Typologies

Communication Technology Usage and Task Complexity Factors for Highly Virtual and Moderately Virtual Typologies

Impact of Virtual Team Typologies on Project Success

Discussion

Conclusion

Appendix

References

Contributors

Acknowledgments

The authors would like to thank PMI for funding this research and also thanks go to Kristin Dunn, Dr. Carla Messikomer, and Juan C. Nogueira, for their guidance and direction on the content and format of this report.

Executive Summary

This report presents empirical evidence to support the existence of a typology framework for virtual project teams. In addition, the relationship between virtual team types and project success is explored.

The following research questions are posed:

1. Using a set of virtual project team attributes based on published research, can virtual team typologies be identified by empirical investigation of data gathered from a large-scale sample of the project work environment?

2. Is there empirical evidence that relationships exist between team demographics and the team typologies identified from research question 1?

3. Do the identified team typologies have specific impacts on the performance of virtual project teams?

These questions are answered using a grounded exploratory research method. A quantitative survey was distributed using SurveyMonkey© to the study population of the chapter members of PMI (which is a target size of 227,646 as of July 2012). The questionnaire was developed based on a review of the literature, which identified eight key characteristics for virtual teams: temporal, geographic, culture, social, political, team membership, technology, and task. The questionnaire was completed by 521 respondents.

Hard (quantitative—e.g., number of team members) and soft (qualitative—e.g., team vision and goals) attributes were defined for the eight key characteristics. Component factor analysis was used to reduce the soft attributes to nine factors:

1. Dedicated team members

2. Virtual team experience

3. Team leader status

4. Team status

5. Vision and goals

6. Experience and knowledge

7. Common processes

8. Cultural awareness

9. Cultural adaptiveness

Based on these nine factors, cluster analysis was performed on the data. Three distinct clusters were identified: Cluster 1 (84 teams) is called virtually challenged, as all attribute mean factor scores are below the sample mean; Cluster 2 (232 teams) is called virtually enhanced, as all attribute mean factor scores are above the sample mean; and Cluster 3 (194 teams) is called virtually neutral. The remainder of the study focuses on the first two clusters, virtually challenged and virtually enhanced teams.

A small-scale study of 50 practitioners with experience working on virtual teams was conducted in order to establish working definitions for high and moderate levels of virtuality. Two physical (hard) attributes were found to define the level of virtuality of a team: 1) the maximum number of hours’ difference in time zones between two locations for the virtual team; and 2) the number of team locations existing for the virtual team. These attributes and their distribution within the data set were used to identify highly virtual teams (more than four team locations and a difference of more than six hours between any two locations) and moderately virtual teams (fewer than four team locations and a difference of six hours or fewer between any two locations). Based on these definitions, the 521 survey responses were classified as highly virtual (134 responses, 26%) and moderately virtual (107 responses, 21%).

Highly virtual teams were found to be significantly different from moderately virtual teams in terms of their team demographics, but not in their ability to manage virtual projects. In contrast, virtually challenged teams are demographically similar to virtually enhanced teams, but report significantly more problems in managing virtual projects.

Finally, this study examined the impact of the proposed virtual project typology on project success. Four questions, based on the project management triple constraints, were used to assess project success: 1) schedule, 2) budget, 3) quality and performance objectives, and 4) client expectations; these were measured using a five-point Likert scale. No significant differences were found between the performances of highly and moderately virtual teams. But virtually enhanced teams performed significantly better on all four measures than virtually challenged teams.

The key findings of this research are: 1) a typology for virtual teams has been developed based on nine factors and has been shown to differentiate between successful and unsuccessful project outcomes; and 2) the degree of physical virtuality has been found to have no impact on project success.

This research contributes to the management of virtual project teams by providing practitioners with a virtual project team typology that results in significantly higher rates of project success. The characteristics of this typology are:

1. Dedicated Team: Team members are dedicated to the project, having dedicated roles or reporting directly to the project leader.

2. Virtual Team Experience: The team members have previous experience working on virtual teams and have previously worked together.

3. Team Leader Status: The team leader is very well known, has achieved recognition, and has a very high degree of interaction within the team and within the organization to which the team belonged.

4. Team Status: The team has a strong reputation for having the political power to get things done and is likely to be allowed the freedom to run the project as it wishes.

5. Vision and Goals: The team has a strong and clearly defined vision, goals and objectives, and team members are strongly aligned to them.

6. Expertise and Knowledge: Team members’ expertise and knowledge is considered much more important than job title/position, and team members are strongly encouraged to actively share their knowledge with the rest of the team.

7. Common Processes: The team has one set of organizational policies, methodologies, and processes.

8. Cultural Awareness: The team members are good at recognizing the different cultural situations that arise within the team and understand the different economic, social, and legal conditions of the various countries in which the other team members live.

9. Cultural Adaptiveness: Team members work hard to adapt to the different cultural situations that occur within the team and are sensitive to other team members’ cultural behaviors. This is reflected in the way team members communicate and interact within the team.

The research contributes to researchers’ knowledge of virtual project teams by providing empirical evidence of a typology for virtual project teams and establishing a link between virtual team typology and project success.

Introduction

The need for project teams to work on a global level has increased (McDonough, Khan, & Barczak, 2001). For many teams, working as a group of colocated people is no longer the norm; instead, people find that teamwork occurs across many time zones, locations, and organizations (Badrinarayanan & Arnett, 2008). This type of teamwork has led to the development of the term “virtual team.” Kirkman, Rosen, Gibson, Tesluk, and McPherson (2002) link the start of the virtual team to the early 1990s when United States multinationals and their affiliates overseas began using the team concept in order to integrate their work practices. Increased globalization and rapid improvements in communication technology have resulted in growth in the use of virtual teams, with Martin, Gilson, and Maynard (2004) contending that nearly all organizational teams are virtual to some extent, while Johnson, Heimann, and O’Neill (2001) state that we have moved away from working with people who are in visual proximity, and toward working with people around the globe. It is therefore important that the working and functioning of virtual teams is better understood.

This report aims to contribute to our understanding of virtual teams and project management by surveying the project management population to see if it is possible, using physical and soft attributes of virtual teams (defined from the academic literature), to empirically identify virtual project team typologies. Unlike previous research that has tended to focus on specific aspects or topics of virtual teams, this research provides a broad view of virtual project teams. Additionally, this study was conducted globally, across multiple companies and industry sectors, gathering information from practicing project managers.

While research studies to date are diverse in terms of their disciplinary focus (Gilson, Maynard, Jones Young, Vartiainen, & Hakonen, 2015), it is difficult to identify empirical research that focuses solely on the project management of virtual project teams. This report provides insights into this field of study in the following of ways:

Identifying virtual project team typologies and their relationships with one another, which will assist in the management of virtual project teams.

Providing information on the impact of a virtual project team typology on overall project success, which will aid in the development of virtual project teams that can support project success.

The respondents to the survey are a sample of the global PMI community and, as such, the data gathered provide insight into how project managers work within virtual project teams.

The specific aims of this research are:

1. To find empirical evidence that there are typological patterns in the virtual project teams being used to execute projects in the current work environment,

2. To establish if demographic trends exist in the application or usage of the various virtual project team typologies identified, and

3. To provide empirical evidence that virtual project team typology influences project success.

By providing practitioners with evidence of the existence of virtual project team types and information on the usage and impact on team performance, project practitioners will be able to:

Classify their project teams against the virtual project team types

Understand the specific challenges associated with managing different virtual project team types

Take action to address these challenges

This will be achieved by answering the following three research questions:

Research Question 1: Using a set of virtual project team attributes based on published research, can virtual team typologies be identified by empirical investigation of data gathered from a large-scale sample of the project work environment?

Research Question 1 will be answered through a detailed review of the literature on virtual teams identifying common attributes and characteristics that have been used in earlier studies.

Research Question 2: Is there empirical evidence that relationships exist between team demographics and team typologies identified from Research Question 1?

The second element of this research is the exploration of relationships between virtual team demographics and the various team typologies identified in Research Question 1.

Research Question 3: Do the identified team typologies from Research Question 1 have specific impacts on the performance of virtual project teams?

The third research question investigates the impacts that identified team typologies have on the performance of virtual project teams. For this research, performance is perceived as the achievement of the standard project triple constraints—time, cost, and quality—in addition to client satisfaction.

The report is structured as follows: A review of the literature on virtual project team characteristics. Identifying core themes is presented, followed by a description of the research methodology employed and the development of a survey addressing these themes. The survey results and analysis are then described and, finally, a discussion of the findings and their implications for both managers and researchers concludes the paper.

Background

While research into virtual teams is considerable, the research effort and resulting academic papers tend to focus on specific aspects or topics of virtual teams, with the result that there is little empirical research that studies virtual teams from a general project management perspective. Some notable exceptions to this are five surveys that use project managers as their population sample (Curlee, 2008; Anantatmula & Thomas, 2010; Bourgault, Drouin, & Hamel, 2008; Henderson, 2008; Verburg, Bosch-Sijtsema, & Vartiainen, 2013).

Empirical research on virtual teams centers on a number of methodologies and themes. The research conducted for this report found that the main research methodologies were case studies, experiments, and qualitative and quantitative surveys. Key topics using case study research are communication and leadership. Experimental or laboratory experiments tend to focus on the communication, cultural, and leadership aspects of virtual teams. Qualitative research uses interviews, study team challenges, culture, and team structure, while quantitative research uses surveys that focus mostly on dispersion, team effectiveness, and performance, as well as on traditional versus virtual teams. An extensive review of the literature on virtual project teams was conducted for this study and is summarized in the Appendix. The literature presented in the Appendix suggests that there are eight key areas of focus in the characteristics of virtual teams. These are summarized below:

Temporal

It is evident that temporal and geographic distributions are key characteristics of virtuality, and it can be argued that these two represent the unique elements of virtuality (Schweitzer & Duxbury, 2010). Most of the focus on the temporal boundary is due to the complexity caused by having numerous team members in different time zones and the difficulty this causes in managing work activities (Chudoba, Lu, Watson-Manheim, & Wynn, 2003). Bell and Kozlowski (2002) look at the impact of task complexity on the time boundary and propose that the greater the complexity, the greater the need for the team to work in a common time zone. The influence of culture from the aspect of time perception and the impact of time being culturally bound is also considered (Connaughton & Shuffler, 2007; Saunders, Van Slyke, & Vogel, 2004). To investigate the temporal characteristics, the research poses a number of questions. The questions investigated if team members existed in different time zones, the largest time differences between team locations, and the number of extra hours that workers worked due to differences in time zones. Questions also focus on the impact temporal dispersion had on task execution, the lack of understanding of the different team members’ physiological and social norms and habits, and delays in accomplishing tasks and meeting deadlines due to confusion over time.

Geographic

All the research has geographical dispersion as a trait of a virtual team. The degree of dispersion is a key area of study. Earlier studies contrasted traditional teams (i.e., colocated, not dispersed) against purely virtual teams (100% dispersed) (Davidow & Malone, 1992; Fulk & DeSanctis, 1995; Townsend, De Marie & Hendrickson, 1998). Later, there is a consensus that virtuality is better studied as a multidimensional continuum between the extremes of traditional and purely virtual (Bell & Kozlowski, 2002; Fiol & O’Connor, 2005; Griffith & Neale, 2001). The main impact of geographical dispersion is the effect on the team in the absence of proximal face-to-face interaction (Griffith & Neale, 2001). Many studies focus on distance in miles, number of sites per team, percentage of team members alone at locations, and subgroups (Hoch & Kozlowski, 2014; O’Leary & Cummings, 2007; O’Leary & Mortensen, 2010). The aspects of geographical distribution studied in this research are the number of team locations, the geographical distribution of the locations, and the structure of the team membership across the locations. The existence of a primary or key location for the team and determining if face-to-face team meetings ever took place is also explored.

Cultural

The research into the culture of virtual teams can be classified into four categories—national, organizational, functional, and team. Given that many virtual teams are spread across many countries, national cultures and their inherent diversity are a key focus of study (Gibson & Cohen, 2003; Dube, Bourhis, & Jacob, 2006; Espinosa, DeLone, & Lee, 2006; Schlenkrich & Upfold, 2009; Watson-Manheim, Chudoba, & Crowston, 2002). However, equal importance is given to the impact of the diverse organizational and functional cultures that also exist within virtual teams (Gibson & Cohen, 2003; Espinosa et al., 2006; Schlenkrich & Upfold, 2009; Staples & Cameron, 2005). Some research also lists gender diversity (Schlenkrich & Upfold, 2009) and language differences (Gibson & Cohen, 2003; Espinosa et al., 2006) as traits of virtual teams. Other research investigates the perceptions of team members on culturally diverse virtual teams with respect to team processes and outcomes (Mockaitis, Rose, & Zettinig, 2012) and the impact of perceived cultural differences in forging identity in virtual teams (Au & Marks, 2012). Glikson and Erez (2013) study the perceived emotional display norms for culturally homogeneous and multicultural teams. To study the cultural characteristics of virtual teams, the aspects investigated were the number of team languages, the use of a mandatory language, the number of nationalities, the number of organizations, functional departments, and the subject matter experts involved in the team. The subjective aspects of cultural characteristics studied were cultural awareness and adaptiveness, use of organizational processes, the level of integration of functional department team members, and subject matter experts of the team.

Social

For the social boundary, the key themes are common goals and shared leadership. Orlikowski’s (2002) boundary list resulted from his study of the Kappa organization. The boundaries explored are those that study participants repeatedly referred to as shaping and challenging their everyday work. The social boundary was the result of hundreds of people engaged in joint development work. The central social theme from the literature is the need for a common goal and objectives (Bal & Teo, 2000; Geber, 1995; Henry & Hartzler, 1997; Lipnack & Stamps, 2000; Nader, Shamsuddin, & Zahari, 2009; Schlenkrich & Upfold, 2009). Lipnack and Stamps (2000) identify the importance of shared leadership, as does Dube et al. (2006) in their proposed 18-structured characteristics of virtual communities of practices. Moser and Axtell (2013) stress the importance of developing shared social norms in virtual teams. The interpersonal relationships within a virtual team are studied from the concept of coopetition (cooperation and competition coexisting) by Baruch and Lin (2012). The characteristics used to examine the social aspects of virtual teams were the existence of a team vision and goals, the alignment to these vision and goals, formal job roles versus expertise and knowledge, and the level of knowledge sharing.

Political

Due to the increased level of boundary-crossing interactions (Bal & Teo, 2000; Lipnack & Stamps, 2000) and the greater number of interactions and affiliations between organizations and the multileveled relationships within them (Watson-Manheim et al., 2002) that are common in virtual teams, politics plays an important role in the functioning of those virtual teams. Mukherjee, Lahiri, Mukherjee, and Billing (2012) use transactional and transformational leadership theories to study leadership capabilities in the various phases of virtual team stages. Zander, Mockaitis, and Butler (2012) propose three themes for global team leadership—leaders and boundary spanners, bridge makers and blenders, people-orientated leadership, and leveraging diversity. The exploration of political characteristics focused on the aspects of team and team-leader political reputation, team autonomy, team-leader interaction with the team and the stakeholder organizations, and the team-leader status.

Team Membership

Team members are a key focus in the research of virtual teams. The central themes for team membership are member skill sets, the temporal nature, or dynamism of the team, and multivariate aspects of the members—multitasking, multicompany, multireporting, and interdependency. There is general consensus that members of virtual teams are skilled knowledge workers (Bal & Teo, 2000; Lee-Kelley, 2002), with Pinjani and Palvia (2013) showing that knowledge sharing mediates the relationship between diversity levels and team effectiveness, and Krumm, Terwiel, and Hertel (2013) studying the different knowledge, skills, and abilities required due to virtual teamwork being based predominantly on electronic collaboration. Many teams are made of members from multiple companies, where team members are contractors and often multitask across teams (Chudoba et al., 2003; Lee-Kelley, 2002; Nader et al., 2009; Schlenkrich & Upfold, 2009; Watson-Manheim et al., 2002; Zhang, Tremaine, Fjermstad, Milewski, & O’Sullivan, 2006). The structure of virtual teams is closely studied, especially the temporary and inconsistent nature of the team membership (Bal & Teo, 2000; Gibson & Gibbs, 2006; Nader et al., 2009, Staples & Cameron, 2005; Wong & Burton, 2000, Maynard, Mathieu, Rapp, & Gilson, 2012; Cummings & Haas, 2012). A considerable amount of the research supports the view that virtual teams are small in size (Bal & Teo, 2000; Dube et al., 2006; Henry & Hartzler, 1997; Martin et al., 2004; Nader et al., 2009). Berry (2011) argues that the skill sets required for team members in virtual teams are more complex than those required in traditional face-to-face teams, while both Robert (2013) and Wang, Waldman, and Zang (2014) study the impacts of shared leadership in virtual teams. The aspects used to study team members were the number of fully dedicated team members and dedicated roles, the number of contractors on the team, and the number of team members that reported directly to the team leader. Also explored were team members’ experiences of working on virtual teams and working with other team members and the diversity of knowledge among the team members.

Communication Technology

All virtual teams utilize computerized media communication. Bal and Teo (2003) view technological communications in the way they enable the team. Lee-Kelley (2002) highlights the extensive use of technology for communication, information, and coordination purposes in order to overcome the constraint of geographical dispersion. Other researchers’ emphasis is on technological dependency—the greater the geographic dispersion, the greater the dependency (Gibson & Cohen, 2003; Dube et al., 2006; Zhang et al., 2006). Han, Hiltz, Fjermestad, and Wang (2011) investigate if there are significant differences in the way virtual teams function. Kozlowski’s (2003) virtual team typology model suggests that a virtual team executing a complex task requires a rich communication medium. A key concern is that electronically mediated communication may hinder understanding and complicate knowledge transfer, especially with information that is complex and ambiguous (Gibson & Gibbs, 2006; Schlenkrich & Upfold, 2009). Klitmoller and Lauring (2013) show that certain types of media are more useful for certain types of knowledge sharing, depending on the different cultural and linguistic variations in virtual teams. Duranti and de Almeida (2012) examine the adequacy of communication tools in diverse culture groups, while Dekker, Rutte, and Van den Berg (2008) study interaction behaviors of cultural groups. Daim, Ha, Reutiman, Hughes, Pathak, Bynum, and Bhatla (2012) list technology as one of the five distinct areas that contribute to communication breakdown in virtual teams. The impact of time, pressure, and use of communication media combined is studied by Caballer, Gracia, and Peiró (2005). To study communication technology, the research examined the characteristics and level of usage of the following technologies—email, instant messaging, video and web conferencing, phone, remote access tools, web portals, data-sharing repositories, social networks, and letters.

Task Complexity

The nature of the task being conducted by the virtual team is considered important in the research literature. Task design, composition, interdependency, conflict, and complexity impact the makeup and functioning of teams (Bell & Kozlowski, 2002; Connaughton & Shuffler, 2007; Espinosa et al., 2006; Martin et al., 2004; Staples & Cameron, 2005; Wong & Burton, 2000; Martinez-Moreno, Zornoza, González-Navarro, & Thompson, 2012). Some authors classify the tasks performed by virtual teams as orientating from the operational to the strategic (Espinosa, DeLone, & Lee, 2006; Lee-Kelley, 2002), with Wong and Burton (2000) describing them as novel, and Schlenkrich and Upfold (2009) describing them as nonroutine. Gratton and Erikson’s (2007) task complexity test was used to study task complexity. This test examines the physical aspects of complexity, such as required team skills, the need to establish a new group to complete the task, dependency on individuals, time pressure, and uncertainty.

These eight key areas provide a broad understanding of the characteristics of virtual teams; however, the development of a virtual team typology also addresses the degree of virtuality of a project team.

Team Virtuality

It is evident that temporal and geographic distributions are key characteristics of virtuality, and it can be argued that these two represent the unique elements of virtuality (Schweitzer & Duxbury, 2010). Most of the focus on the temporal boundary is the complexity caused by having numerous project team members in different time zones and the difficulty this causes in managing work activities (Chudoba et al., 2003). Bell and Kozlowski (2002) look at the impact of task complexity on the time boundary and propose that the greater the complexity, the greater the need for the team to work in a common time zone. The influence of culture from the aspect of time perception, and the impact of time being culturally bound is also considered (Connaughton & Shuffler, 2007; Saunders, Van Slyke, & Vogel, 2004). Geographical dispersion is universally accepted as a trait of a virtual team. The degree of dispersion is a key area of study. As stated in the earlier section on geographic dispersion, prior studies contrasted traditional project teams (i.e., colocated, not dispersed) against purely virtual teams (i.e., 100% dispersed) (Davidow & Malone, 1992; Fulk & DeSanctis, 1995; Townsend, De Marie, & Hendrickson, 1998). Later, there is a consensus that virtuality is better studied as a multidimensional continuum between the extremes of traditional to purely virtual (Bell & Kozlowski, 2002; Fiol & O’Connor, 2005; Griffith & Neale, 2001). The main impact of geographical dispersion is the effect on the team of the absence of proximal face-to-face interaction (Griffith & Neale, 2001).

This review of literature examining virtual project teams proposes a set of attributes that can be used to develop a typology for virtual project teams. The next section will describe how these attributes were applied to develop the survey instrument that was used to gather empirical data and how the attributes were refined in order to develop virtual project team typologies.

Methodology

The research method used was grounded exploratory research using a quantitative survey. The survey tool was SurveyMonkey© and study population was PMI chapter members. This is a target size of 227,646 (as of July 2012). Using the PMI chapter member’s advisory group and PMI chapter mentors, the survey was distributed to all chapter members. The total number of responses collected was 521, which represents the sample size of the study. An original questionnaire was developed based on the frameworks outlined in the literature review. The eight data categories for the questionnaire that emerged from an extensive review of the literature are: temporal, geographic, culture, social, political, team membership, technology, and task. The survey also gathered data to measure project team performance, in order to analyze the impacts of key virtual team attributes on performance. Cluster analysis, based on soft attributes, or factors, identified two types of virtual teams: virtually enhanced and virtually challenged. Quantitative information was used to define a typology based on the degree of virtuality; moderately virtual and highly virtual teams were identified. Finally, the impact of these virtual team types on project success was explored.

Development of Research Instrument

Table 1 summarizes the eight characteristics used to investigate virtual teams and outlines the hard and soft attributes that were used to develop a survey instrument with which to study the typology of virtual project teams. For the purpose of this research, hard attributes are inherent attributes of the team, or attributes that can be clearly quantified, for example, the number of people on the virtual project team. On the other hand, soft attributes are more likely to describe the qualitative characteristics of the project team; for example, the experiences of the team members. The soft and hard factors were used to define virtual team typologies based on empirical evidence from the survey data.

The survey used four questions, based on Pinto and Slevin (1988), to assess project success:

The project was completed on schedule.

The project was completed within or on budget.

The project achieved its quality and performance objectives.

The project deliverables met client expectations.

Each respondent was asked to complete the questionnaire based on a project that was recently completed by a virtual team of which they were a member.

Virtuality Measure

In addition to the main survey described above, a further small-scale study of 50 practitioners with experience working on virtual teams was used in order to establish a working measure of virtuality. This research found that two attributes are deemed to have the most impact on the level of virtuality of a team: 1) the number of hours’ difference in time zones between the two locations of the virtual team; and 2) the number of team locations existing for the virtual team. This definition was used to identify the level of virtuality of teams within the study.

Key Characteristic Hard Attribute Soft Attribute

Temporal dispersion

  • Team members in different time zones
  • Time difference between time zones
  • Extra hours worked
  • Difficulty of task execution
  • Impact on functional or workshop relationship between team members
  • Lack of understanding of different physiological and social habits or norms
  • Time delays cause confusion
Geographic dispersion
  • Number of locations
  • Key location
  • Geographical distribution of locations
  • Team structures at locations

Cultural

  • Number of languages
  • Mandatory language
  • Number of nationalities
  • Number of organizations
  • Number of functional departments
  • Number of subject matter experts
  • Recognizing different cultural situations
  • Understanding different economic, social, and legal conditions
  • Adapting to different cultural situations
  • Sensitivity to cultures reflected in communication and interaction
  • Dominance of organizations
  • Use of organizational processes
  • Integration of functional department members and subject matter experts into the team
Political  
  • Team and team leaders’ political reputation and standing
  • Team autonomy and freedom
  • Team leaders’ interactions with team and team organizations
Social  
  • Team vision and goals
  • Alignment to vision and goals
  • Formal job role versus expertise and knowledge
  • Knowledge transfer and sharing
Team membership  
  • Experience of working on virtual teams
  • Experience of working with other team members
  • Diversity of knowledge
  • Number of fully dedicated members
  • Number with dedicated roles
  • Number reporting directly to team leader
  • Number of contractors
Communication technology  
  • Experience of using communication technology
  • Usage of communication technologies
Task complexity  
  • Team skills
  • New group required
  • Dependency on individuals
  • Uncertainty
  • Time pressure

Table 1: Eight key characteristics of virtual teams.

Data Analysis

Data analysis was conducted in three phases. First, component factor analysis was conducted on the virtual team characteristic data to identify the soft attributes of virtual project teams. Cluster analysis was then preformed to identify the teams that had positive or enhanced attributes and those that had challenging attributes. Second, based on the measure of virtuality defined above, the sample was divided into those project teams that were “highly virtual” and those that were “moderately virtual.” (Note: All teams were virtual to some extent, as this was a prerequisite for participating in the study.) Finally, the impact of both virtuality and team characteristics on project success was examined.

Results

Results are presented in five parts. First, an overview of the demographic data is presented and then a virtual team typology is proposed based on the empirical data. Next, the different types of virtual teams are compared (virtually challenged versus virtually enhanced and moderately virtual versus highly virtual), in terms of how they manage projects. Finally, the relationship between the virtual team typology and project success is examined.

Demographic Results

Table 2 shows the spread of nationalities that responded to the survey. Irish and Americans are the top two respondents, making up a total of 183. This is not unexpected given that the authors are Irish and the largest numbers of PMI members are located in the United States.

Country Number of Responses
Ireland 106 (20%)
United States 77 (15%)
India 35 (7%)
England 31 (6%)
France 17 (3%)
Belgium 15 (3%)
Others: Canada, Sweden, Portugal, Germany, Poland, Croatia, Italy, Philippines, Brazil, Australia, Ghana, Mexico, South Africa, Colombia, Netherlands, Switzerland, Greece, Indonesia, New Zealand, Sri Lanka, Thailand, Austria, Costa Rica, Malaysia, Nigeria, Pakistan, Argentina, Bulgaria, Chile, China, Czech Republic 239 (46%)

Table 2: Nationality of respondents.

The respondents were asked to class their organization as multinational, country indigenous, or consultancy. Multinational organizations had the highest representation at 67.4%, indigenous organizations made up 17% of the sample, and consultancies accounted for 13% (3% selected “other”). The spread of the respondents according to industry sector is shown in Table 3. The predominant industry focuses are information technology (24%) and telecommunications (10%).

Industry Sector Number of Responses
Information Technology 125 (24%)
Telecommunications 53 (10%)
Financial Services 34 (7%)
Manufacturing 33 (7%)
Consulting 32 (6%)
Engineering 32 (6%)
Others: Resources, Government, Insurance, Pharmaceuticals, Healthcare, Utility, Construction, Aerospace, Business Services, Food and Beverage 202 (39%)

Table 3: Industry sector.

Table 4 shows a breakdown of the sample by project cost and duration. The survey findings show that over 63% of the projects executed by the virtual teams cost under US$5 million and that 53% of the projects have a duration of between six months and two years.

Finally, Table 5 shows the research sample by organization size. This shows that 60% of the organizations in which the respondents worked employed 20,000 or less.

The main story that the demographic data tells is that virtual project teams are used across national boundaries, industry sectors, in firms of all sizes, and on projects of all durations and costs.

Cost of Project (US$) Number of Responses Duration of Project Number of Responses
>10 million 82 (17%) <= 3 months 42 (9%)
>5 million <= 10 million 33 (7%) >3 months <= 6 months 88 (18%)
>1 million <= 5 million 94 (20%) >6 months <= 1 year 125 (26%)
>300,000 <= 1 million 90 (19%) >1 year <= 2 years 130 (27%)
<= 300,000 119 (25%) >2 years 94 (20%)
unknown 61 (13%)    

Table 4: Industry sector.

Organization Size Distribution (People) Number of Responses
<= 1,000 147 (31%)
>1,000 <= 20,000 140 (29%)
>20,000 <= 50,000 45 (9%)
>50,000 <= 100,000 47 (10%)
>100,000 84 (18%)
Unknown 16 (3%)

Table 5: Organization size.

Empirically Based Virtual Team Typologies

Component factor analysis was used on the data gathered to reduce the soft attributes to nine common factors; these are detailed in Table 6. Initially, temporal dispersion characteristics were also intended to be used in the cluster analysis. However, on review, the nature of the survey questions for temporal distribution and the resulting factors defined from the factor analysis were deemed to be “output” characteristics that result from temporal dispersion, rather than “input” characteristics inherent in the virtual team. Similarly, usage of communication technology was also viewed as an “output” characteristic and not included in the cluster analysis. The format of the questions on task complexity and the two questions associated with the “soft” factors for geographical dispersion were not suitable for factor analysis and, thus, they were not included in the cluster analysis. The relationship between the nine identified soft factors and the removed soft attributes (temporal dispersion, use of communication technology, geographical dispersion, and task complexity) are presented later in this report.

Virtually Enhanced and Virtually Challenged Typologies

A cluster analysis was conducted on the data set with the nine soft factors identified in Table 7 in order to identify whether teams could be grouped based on these factors. Using K means cluster analysis, three clusters were identified (Table 3). Cluster 1 (N = 84) can be identified as the group with the factor scores for all the factors below the mean; Cluster 2 (N = 232) is the group in which the factor scores are above the mean; and Cluster 3 (N = 194) is the group with a mix of factor scores above and below the mean. These are labeled as virtually challenged (below the mean), virtually enhanced (above the mean), and virtually neutral (a mix of above and below mean). For the purpose of this research, only the first two cluster typologies are investigated.

A detailed description of the differences between virtually challenged and virtually enhanced typologies is given in Table 8.

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Table 6: Nine soft factors of virtual teams.

Attribute Cluster 1 (N=84) Cluster 2 (N=232) Cluster 3 (N=194) Mean
Dedicated team members −0.06 0.35 −0.39 3.8
Virtual team experience −0.23 0.45 −0.43 3.4
Team leader status −0.85 0.28   0.01 3.9
Team status −0.46 0.45 −0.36 3.3
Vision and goals −1.63 0.37   0.21 3.8
Expertise and knowledge −0.10 0.40 −0.45 3.9
Common processes −0.86 0.43 −0.16 3.5
Cultural awareness −0.47 0.56 −0.47 3.4
Cultural adaptiveness −0.79 0.24   0.04 3.5

Table 7: Virtually challenged and virtually enhanced clusters.

Highly Virtual and Moderately Virtual Typologies

In the previous section, two distinct typologies (virtually challenged and virtually enhanced) were empirically defined, based on a cluster analysis of the soft factors of a virtual team. The next step in the research is to define typologies based on the hard attributes of virtual teams.

In order to establish a working measure of virtuality, a further, small-scale study of 50 practitioners experienced with working on virtual teams was conducted. This research found that two physical (hard) attributes are deemed to have the most impact on the level of virtuality of a team: 1) the number of hours’ difference in time zones between two locations for the virtual team; and 2) the number of team locations existing for the virtual team.

The quartile figures for these two attributes from the main data set (the 521 responses) were then used to classify teams as highly virtual or moderately virtual. These are defined as follows:

Highly virtual: The difference in time zones between two locations is greater than six hours, and the number of team locations is greater than four.
Moderately virtual: The difference in time zones between two locations is fewer than six hours, and the number of team locations is less than four.
Attribute Virtually Challenged Virtually Enhanced
Dedicated team members
  • The team members are less likely to be dedicated to the project, have a dedicated role, or report directly to the project leader.
  • The team members are dedicated to the project, have a dedicated role, or report directly to the project leader.
Virtual team experience
  • The team members are less likely to have experience working on virtual teams and are unlikely to have worked together.
  • The team members have previous experience working on virtual teams and have previously worked together.
Team leader status
  • The team leader or leaders were well known, have achieved recognition, and have a high degree of interaction within the team and within the organization or organizations to which the team belonged.
  • The team leader or leaders were very well known, have achieved recognition, and have a very high degree of interaction within the team and within the organization or organizations to which the team belonged.
Team status
  • The team is likely to have a strong reputation for having the political power to get things done and is likely to be allowed the freedom to run the project as it wishes.
  • The team has a strong reputation for having the political power to get things done and is likely to be allowed the freedom to run the project as it wishes.
Vision and goals
  • The team has a clearly defined vision, goals, and objectives, and team members are aligned to them.
  • The team has a strong and clearly defined vision, goals, and objectives, and team members are strongly aligned to them.
Expertise and knowledge
  • Team members’ expertise and knowledge is considered more important than job title or position, and team members are encouraged to, and willingly share their knowledge with the rest of the team.
  • Team members’ expertise and knowledge is considered much more important than job title or position, and team members are strongly encouraged to, and actively share their knowledge with the rest of the team.
Common processes
  • The team is likely to have one set of organizational policies, methodologies, and processes.
  • The team has one set of organizational policies, methodologies, and processes.
Cultural awareness
  • The team members are likely to be good at recognizing the different cultural situations that arise within the team and are likely to understand the different economic, social, and legal conditions of the various countries in which the other team members lived.
  • The team members are good at recognizing the different cultural situations that arise within the team and understand the different economic, social, and legal conditions of the various countries in which the other team members lived.
Cultural adaptiveness
  • Team members are likely to work hard to adapt to the different cultural situations that occur within the team and are likely to be sensitive to other team members’ cultural behaviors. This is likely to be reflected in the way team members communicate and interact within the team.
  • Team members work hard to adapt to the different cultural situations that occur within the team, and are sensitive to other team members’ cultural behaviors. This is reflected in the way team members communicate and interact within the team.

Table 8: Cluster description table.

Of the 521 survey responses, 241 met either the highly virtual or moderately virtual criteria listed above. Figure 1 shows 21% of the sample can be classed as belonging to the moderately virtual typology and 26% can be classed as belonging to the highly virtual typology.

The differences between the highly virtual and moderately virtual typologies across the nine soft factors of virtual teams are shown in Table 9. Only one factor is significantly different—dedicated team, with moderately virtual teams having a higher degree of dedicated team members than highly virtual teams.

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Figure 1: Highly versus moderately virtual selection criteria.

In summary, the analysis shows that:

Component factor analysis performed on the survey data defines nine attributes to study the typology of virtual teams—dedicated team members, virtual team experience, team leader status, team status, team vision and goals, team expertise and knowledge, common processes, cultural awareness, and cultural adaptiveness. Using the nine factors, two distinct typologies are identified, which are labeled virtually challenged and virtually enhanced. A team in the virtually challenged cluster is a team that registers below-mean responses for the nine attributes. A team in the virtually enhanced cluster is a team that registers above-mean responses for the nine attributes.

Based on a secondary survey, the greatest difference in time zones and number of locations were the two physical characteristics of virtual teams that have the most impact on the level of virtuality. Based on the quartile percentage findings for the survey questions on difference in time zones and number of locations, two further typologies were identified—highly virtual and moderately virtual.

In the previous section, four typologies were identified. The next two sections will examine the relationship between these typology groups and other team demographics.

  Moderately Virtual Mean Highly Virtual Mean T-Test (Two-Tailed)
Dedicated team 4.26 3.51 0.000**
Virtual Team Experience 3.48 3.49 0.946
Team Leader Status 3.79 3.96 0.055
Team Status 3.27 3.42 0.153
Vision and Goals 3.75 3.9 0.120
Expertise and Knowledge 3.99 4.03 0.592
Common Processes 3.39 3.58 0.266
Cultural Awareness 3.49 3.4 0.383
Cultural Adaptiveness 3.53 3.53 0.990

Table 9: Comparisons of nine soft factors in highly virtual and moderately virtual teams.

Virtually Challenged Versus Virtually Enhanced Team Comparisons

The key physical attributes of the team structure of virtually challenged and virtually enhanced teams are compared in Table 10. The number of people on the team is the only physical team-structure attribute that shows a statistically significant difference between the two groups of teams. However, if the mean and median values for the other team structure attributes are examined, differences between the two clusters are evident.

The median for the “number of team locations” is slightly higher for the virtually enhanced team group than the virtually challenged team group.

For the “largest time zone difference,” the mean of the virtually enhanced group is slightly higher than the virtually challenged group mean.

The mean of the virtually challenged cluster for the “number of nationalities” is slightly higher than the virtually enhanced mean.

The number of functional departments has a higher mean value for the virtually challenged cluster.

The mean for the number of subject matter experts is higher for the virtually enhanced group.

The findings from the comparison of virtually challenged and virtually enhanced team structures show that there is little difference between the team structures of the two typologies. The expectation that the two typologies would be significantly different with regard to number of team members, number of locations, number of organizations, number of subject matter experts (SME), and number of nationalities does not hold true. Thus, these are not the causal reasons for a team being virtually challenged or virtually enhanced.

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Table 10: Challenged/enhanced team-structure comparison mean and t-test.

The survey asked many questions relating to the physical makeup of the virtual team, such as where members of the same nationality, time zone, and organization did their face-to-face meetings, whether or not a key location and mandatory language exist. As the question scoring used yes/no questions and Likert scales, a nonparametric chi-squared test was used to compare the two clusters, Table 11 shows these findings.

From Table 11, we can see that there is little difference between virtually challenged and virtually enhanced teams with regard to team structure, team operation processes, project type, and project organization. In fact, only three factors are identified as having statistically significant differences. These are:

Face-to-face meeting occurred that involved all of the team members

The cost of the project

Knowledge diversity of the team members

These three factors will now be analyzed in more detail.

Demographic Pearson Chi-Squared Test for Difference Challenged/Enhanced
Team Structure  
All members are the same nationality 0.471
All members in the same time zone 0.385
All members in the same organization 0.917
Knowledge diversity of the team members 0.003**
The makeup of the team members at locations 0.133
Team Operation Processes  
A face-to-face meeting that involved all of the team members took place 0.008**
A main location exists for the team 0.109
There was an official or mandatory team language used 0.936
The leadership structure on the team 0.096
Project Type  
The duration of the project 0.256
The cost of the project 0.010**
Project Organization  
The number of people employed by the organization executing the project 0.718
Classification of organization 0.698
Industry focus 0.761

** Statistically significant difference p<0.5

Table 11: Challenged/enhanced demographic comparison chi-squared test.

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Figure 2: Challenged/enhanced face-to-face meetings held.

Face-to-Face Meeting That Involved Team Members

The bar chart for the findings on face-to-face meetings (see Figure 2) shows that a greater number of virtually enhanced teams had at least one or more face-to-face meetings than virtually challenged teams. Also, the mean value for the number of face-to-face team meetings held by virtually enhanced teams, which is 8.89, is greater that the mean value for virtually challenged teams, which is 6.57. This indicates that enhanced teams are more likely than challenged teams to host face-to-face meetings and are also more likely to have more frequent face-to-face meetings.

The Cost of the Project

The chart of the differences in project costs (see Figure 3) shows that marked variances exist in the categories that cost more than US$5 million and are US$10 million or less and more than US$10 million.

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Figure 3: Comparison of challenged and enhanced project costs.

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Figure 4: Challenged/enhanced knowledge diversity comparison.

Knowledge Diversity of the Team Members

Figure 4 shows that knowledge diversity in enhanced and challenged teams differed. The virtually enhanced teams strongly agreed more than the virtually challenged teams that there was a diversity of knowledge, whereas the virtually challenged teams disagreed more than enhanced teams that there was a diversity of knowledge.

Overall, the findings shown in Table 11 further reinforce that there are few differences between the demographic factors of virtually challenged and virtually enhanced teams.

Temporal Dispersion Factors for Virtually Challenged and Enhanced Typologies

A comparison of the temporal dispersion factors of virtual teams showed a marked difference between virtually challenged and virtually enhanced teams with all factors having statistically significant differences. Table 12 shows that the means for virtually challenged factors are consistently higher than those of virtually enhanced factors. This indicates that challenged teams are more impacted by time-zone dispersion than the virtually enhanced teams.

Challenged teams find doing tasks in parallel more difficult than enhanced teams.

Challenged teams experience more delays in communication than enhanced teams.

The functional and working relationship between team members is negatively impacted by time-zone difference to a greater extent on challenged teams than on enhanced teams.

Challenged teams experience more confusion with clock times than enhanced teams, resulting in missed meetings and task deadlines.

In challenged teams, there is a greater lack of understanding of the different physiological and social norms of the team members than in enhanced teams, and this causes conflict.

Temporal Dispersion Factors Virtually Challenged Mean Virtually Enhanced Mean Pearson's Chi-Squared Test for Difference
Executing tasks in parallel is difficult 3.37 2.78 0.020**
Delays in communication 3.8 2.97 0.000**
Negatively impacted the functional working relationship 3.42 2.33 0.000**
Lack of understanding of the different physiological and social norms 3.41 2.35 0.000**
Lack of understanding of the different physiological and social norms caused conflict 3 2.16 0.000**
Confusion over clock times caused missed scheduled meetings 2.34 1.87 0.003**
Confusion over clock times caused missed task deadlines 2.36 1.73 0.000**

** Statistically significant difference p<0.05

Table 12: Challenged or enhanced temporal dispersion factors comparison.

Communication Technology Usage and Task Complexity Factors for Virtually Challenged and Enhanced Typologies

The research also compared the clusters based on the level of communication usage, Table 13 shows the findings. For usage of communication technology, the only two factors that show statistically significant differences are the experience of using technology and the use of team and organization web portals. It is worth noting that, apart from the use of fixed-line phones, the mean level of usage by enhanced teams for all other factors is higher than the level of usage by challenged teams.

Usage of Communication Technology Virtually Challenged Mean Virtually Enhanced Mean Pearson's Chi-Squared Test
Experience of using communication technology 3.92 4.4 0.000**
Stand-alone video conferencing 1.92 2.05 0.776
Web conferencing 3.24 3.76 0.217
Instant messaging 3.64 4.32 0.152
Remote access and control tool 2.38 2.88 0.250
Email 5.51 5.57 0.656
Fixed telephone 4.5 4.45 0.682
Mobile phone 4.08 4.27 0.351
Letter/Fax 1.51 1.53 0.825
Social networks 1.15 1.54 0.106
Data-sharing repositories 3.7 3.92 0.484
Team and organization web portals 2.59 3.62 0.001**

** Statistically significant difference p<0.05

Table 13: Challenged/enhanced technology usage factors comparison.

The comparison findings for task complexity show that there is no difference in the complexity of tasks that both virtually challenged and virtually enhanced teams perform (Table 14). This shows that the differences between the two clusters cannot be a result of task complexity.

The data from the comparisons of virtually challenged and virtually enhanced teams shows that the main differences between them are those associated with temporal dispersion—executing tasks in parallel, delays in communication, lack of understanding of the different physiological and social norms, and confusion of meeting and task times.

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Table 14: Challenged/enhanced task complexity comparison.

Highly Virtual Versus Moderately Virtual Team Comparisons

The analysis of differences between highly virtual and moderately virtual teams shows that there are differences between the two groups. Table 15 details the findings for the key physical attributes associated with team structure. There are statistically significant differences for the physical team structure factors:

Number of people on the team

Impact on work hours (extra hours worked)

Number of nationalities

Number of organizations involved

Number of functional departments involved

Number of subject matter experts involved

In all cases, the mean and median of the demographic factors of the highly virtual team cluster are higher than the moderately virtual team cluster. This indicates that highly virtual teams tend to have a greater number of people involved and more nationalities, organizations, departments, and subject matter experts that make up the team. Highly virtual teams also work more hours outside business hours than moderately virtual teams.

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Table 15: High or moderate team-structure comparisons-mean and t-test.

Table 16 shows the comparison data findings for team structure, project type, project organization, and project operation processes. As the scores for these questions use yes or no answers and Likert scales, Pearson’s chi-squared test for difference is used, rather than an independent t-test.

The findings show that for moderately and highly virtual teams, they differ in their team structure, project organization, and project organization processes. The analysis shows that eight factors are significantly different for moderately and highly virtual teams. These eight factors are discussed in more detail below.

Face-to-Face Meeting That Involved all Team Members

Of the teams that were classified as highly virtual, 32.8% reported that face-to-face meetings involving all team members took place. This contrasts with 47.6% of the teams classified as moderately virtual—the findings are shown in Figure 5.

Demographic Pearson Chi-Squared Test for Difference Moderately/Highly
Team Structure  
All members are the same nationality 0.000**
All members are in the same time zone N/A
All members are in the same organization 1.000
Knowledge diversity of the team members 0.151
The makeup of the team members at locations 0.000**
Team Operation Processes  
A face-to-face meeting that involved all of the team members took place 0.020**
A main location exists for the team 0.001**
There was an official or mandatory team language used 0.004**
The leadership structure on the team 0.055
Project Type  
The duration of the project 0.104
The cost of the project 0.023**
Project Organization  
The number of people employed by the organization executing the project 0.000**
Classification of organization 0.000**
Industry focus 0.079

** Statistically significant difference p<0.05
Note: N/A, as time-zone difference is a factor in deciding between highly virtual and moderately virtual.

Table 16: High/moderate demographic comparison—Chi-squared test.

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Figure 5: Face-to-face meetings.

This result is not surprising, as highly virtual teams are located farther apart and have more locations, making it more difficult for all team members to meet.

All Team Members Were of the Same Nationality

While moderately virtual teams can be made of the same nationality, no highly virtual teams are made up of the same nationality, see Figure 6.

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Figure 6: Team nationality.

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Figure 7: Mandatory language.

Official Mandatory Language for the Team

Figure 7 shows that nearly 100% of highly virtual teams have a mandatory language policy. Moderately virtual teams mostly have a mandatory language policy, but over 10% state that they do not have a mandatory language.

Existence of a Main location

Figure 8 shows that moderately virtual teams are more likely to have a main/key team location. However, quite a high number of highly virtual teams also have a main team location.

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Figure 8: Main location.

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Figure 9: Makeup of team members at location.

The Makeup of Team Members at Locations

Figure 9 shows that teams with unequal members at each location was the most common team-member structure for highly virtual teams. The most common structure for moderately virtual teams has over 50% of the team at one location.

The Cost of the Project

Figure 10 shows that over 50% of moderately virtual projects cost less than or equal to US$5 million. While highly virtual project costs are more evenly spread across the ranges, over 40% cost more than US$5 million, compared to approximately 20% of moderately virtual projects.

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Figure 10: Project cost.

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Figure 11: Organization size.

Size of the Organization Executing the Project

From Figure 11, it is clear that the majority of moderately virtual teams (80%) belong to organizations of less than 20,000 people. Highly virtual teams are more evenly spread, with approximately 30% belonging to organizations of more than 50,000 people.

Classification of the Project Organization

Highly virtual teams mostly belong to multinationals, whereas moderately virtual teams are more evenly spread, with 25% belonging to country-indigenous companies and 21% belonging to consultancies, see Figure 12.

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Figure 12: Organization classification.

Temporal Dispersion Factors for Highly Virtual and Moderately Virtual Typologies

Comparison of the differences between moderately and highly virtual teams for temporal dispersion factors show that the differences are not as striking as the differences between challenged and enhanced virtual teams. Table 17 shows the findings. Only one factor—executing tasks in parallel is difficult—has a significantly statistical difference between low- and highly virtual teams. However, the mean and median data show that the mean scores for most of the factors for moderately virtual teams are consistently lower than those of highly virtual teams. It is worth noting that for the lack of understanding of physiological and social norms attributes, moderately virtual teams considered these as having more of an impact than highly virtual teams did.

Temporal Dispersion Factors for Low/High Moderately Virtual Mean Highly Virtual Mean Pearson Chi-Squared Test for Difference
Executing tasks in parallel is difficult 2.59 3.26 0.004**
Delays in communication 2.96 3.41 0.101
Negatively impacted the working relationship 2.39 2.69 0.256
Lack of understanding of the different physiological and social norms 2.80 2.65 0.129
Lack of understanding of the different physiological and social norms caused conflict 2.69 2.37 0.358
Confusion over clock times caused missed scheduled meetings 1.86 2.10 0.109
Confusion over clock times caused missed task deadlines 1.78 2 0.315

** Statistically significant difference p<0.05

Table 17: High/moderate temporal dispersion factors comparison.

Communication Technology Usage and Task Complexity Factors for Highly Virtual and Moderately Virtual Typologies

The study of the comparisons between moderately and highly virtual teams for the level of usage of communication technology is outlined in Table 18. Analysis of the data shows that there is little difference between moderately and highly virtual teams in the experience of and use of communication technology. Only the usage of web conferencing tools, instant messaging tools, and data-sharing repositories are different, with highly virtual teams using these tools more than moderately virtual teams.

Usage of Communication Technology Moderately Virtual Mean Highly Virtual Mean Pearson Chi-Squared Test for Difference
Experience of using communication technology 4.20 4.40 0.058
Standalone video conferencing 2.00 1.94 0.054
Web conferencing 3.13 3.95 0.003**
Instant messaging 3.89 4.60 0.044**
Remote access and control tool 3.01 2.80 0.464
Email 5.49 5.63 0.314
Fixed telephone 4.49 4.47 0.54
Mobile phone 4.11 4.02 0.127
Letter/Fax 1.58 1.35 0.211
Social networks 1.42 1.36 0.881
Data sharing repositories 3.45 4.35 0.002**
Team and organisation web portals 3.18 3.46 0.601

** Statistically significant difference p<0.05

Table 18: High/moderate communication technology usage comparison.

There is only one difference between low- and highly virtual teams with regard to task complexity—the task required collective input and agreement from more than 20 people—is significantly different (see Table 19 and Figure 13).

The relationship between moderately virtual and highly virtual, and virtually challenged and virtually challenged enhanced teams are summarized in Table 20.

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Table 19: High/moderate task complexity comparison.

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Figure 13: Collective input complexity factor.

Team Trait Virtually Challenged Versus Virtually Enhanced Moderately Virtual Versus Highly Virtual
Number of team members Team numbers for challenged teams tend to be higher than enhanced teams Team numbers for highly virtual teams tend to be higher than moderately virtual teams
Number of team locations No difference N/A—One of the cluster selection criteria is number of locations
The geographical distribution of the team locations No difference N/A—One of the cluster selection criteria is number of locations
The makeup of team members at locations No difference Moderately virtual teams tend to have over 50% of their team at one team location. Highly virtual teams tend to have unequal team numbers at each team location
Greatest time zone difference between two locations on a team No difference N/A—One of the cluster selection criteria is greatest time difference between two locations
Ratio of the number of teams in the same time zone and in different time zones No difference N/A—One of the cluster selection criteria is greatest time difference between two locations
Number of different nationalities No difference There are more nationalities on highly virtual teams than on moderately virtual teams
Number of different organizations No difference There tends to be more organizations involved on highly virtual teams than are involved on moderately virtual teams
Number of different functional departments No difference There tends to be more functional departments involved on highly virtual teams than are involved on moderately virtual teams
Impact on hours worked—extra hours outside normal business hours worked due to time-zone differences No difference Highly virtual teams do more work outside normal business hours due to time-zone dispersion than moderately virtual teams
Number of different subject matter experts No difference There tends to be more subject matter experts involved on highly virtual teams than are involved on moderately virtual teams
Ratio of the number of teams of the same nationality and of different nationalities No difference Highly virtual teams are never made up of the same nationality, whereas in moderately virtual teams, many of the teams are of the same nationality.
Ratio of teams made up from just one organization and made up of multiple organizations No difference No difference
Likely to have a key location No difference. More than 60% of teams in each group had a key location. Moderately virtual teams are more likely to have a key location than highly virtual teams.
Face-to-face meetings Enhanced teams are more likely to host face-to-face meetings for the entire team. Moderately virtual teams are more likely to host face-to-face meetings for all team members.
Leadership structure—One sole leader versus multiple leaders No difference No difference
Use of a mandatory language No difference Highly virtual teams are more likely to have a mandatory language than moderately virtual teams.
Organization class No difference Moderately virtual teams exist more often than highly virtual teams in consultancies and country-indigenous organizations. Highly virtual teams exist more than moderately virtual teams in multinationals.
Industry focus of the organization No difference No difference
Project cost There are more challenged projects than enhanced projects in the >US$10 million range There more moderately virtual than highly virtual projects in the <=US$0.3 million range
There are more highly virtual than moderately virtual projects in the >US$5 million range
Size of the organization owning the project No difference Moderately virtual teams tend to exist in organizations of <20,000. Highly virtual teams are spread over all organization sizes
Negative impact on temporal dispersion Major difference. Temporal dispersion has a greater negative impact on the workings of challenged teams. No real difference in the impact temporal dispersion has on team working. The only factor where temporal dispersion has greater negative impact is executing tasks in parallel. Highly virtual teams find it more difficult than moderately virtual teams.
Experience of using communication technology Enhanced teams were more experienced in the use of communication technology than challenged teams. No difference
Level of communication technology usage No difference in the level of usage, except for team and organization web portals, of which enhanced teams were more frequent users. Highly virtual teams are greater users than moderately virtual teams of web conferencing, instant messaging, and data-sharing repositories.
Knowledge diversity of the team members Enhanced teams indicate a higher diversity of knowledge than challenged teams. No difference
Task complexity No difference in task complexity No real difference, except for one factor. A higher percentage of moderately virtual teams than highly virtual teams agreed that in order to perform the task required, collective input and agreement from more than 20 people was needed.

Table 20: Team traits comparison.

In summary, the key findings based on the comparisons between virtually enhanced and virtually challenged teams and between highly virtual and moderately virtual teams are:

The impact of temporal dispersion is significantly different between virtually enhanced and virtually challenged teams. Time-zone dispersion has a greater negative impact on challenged teams than on enhanced teams. For highly and moderately virtual teams, there is no difference between the two groups for the impact of temporal dispersion.

While team members of highly virtual and moderately virtual teams show no difference in their experience of using communication technology, highly virtual team members are heavier users of web conferencing tools, instant messaging, and data-sharing repositories. For virtually challenged and enhanced teams, team members from enhanced teams are more experienced than team members from challenged teams in the use of communication technology. Also, enhanced teams are heavier users of team and organization web portals.

There are no differences in the complexity of the tasks executed by the four typologies.

Except for the number of people on the team, no real differences exist between virtually challenged teams and virtually enhanced teams. They both tend to have the same physical team structure, project types, project operation processes, and exist in similar organizations. Highly virtual and moderately virtual teams are different in their physical team structure, with highly virtual teams having a larger number of team members, more nationalities, more organizations, and more functional departments involved, as well as working more hours outside normal business hours.

Virtually enhanced teams are more likely to host a face-to-face meeting for the whole team than virtually challenged teams. Also, enhanced teams hold a greater number of face-to-face meetings than challenged teams. Moderately virtual teams are more likely to hold face-to-face meetings for the entire team than highly virtual teams.

There tends to be a greater diversity of knowledge among team members of virtually enhanced teams than virtually challenged teams. There is no difference in the diversity of knowledge between highly and moderately virtual teams.

There is no difference between virtually challenged and virtually enhanced teams in the use of mandatory language. Highly virtual teams tend to use a mandatory language more so than moderately virtual teams.

Moderately virtual teams are more likely to have a key location than highly virtual teams. For virtually challenged and virtually enhanced teams, there was no difference found with regard to having a key location or not. However, virtually challenged and virtually enhanced teams differed in the team structure at locations. For enhanced teams, the most common structure was unequal members at each location, whereas for challenged teams, the most common structure was greater than 50% of the team at one location.

There was no difference between virtually enhanced and virtually challenged teams with regard to organization size and industry classification. Highly and moderately virtual teams did differ. More highly virtual teams existed in large organizations, whereas more moderately virtual teams existed in smaller organizations. The main industry class of highly virtual teams was multinational, and while the main industry class of moderately virtual teams was also multinational, teams also existed in country-indigenous and consultancy.

Moderately virtual team project costs tended to be less than US$5 million, while highly virtual projects costs are more evenly spread across the ranges, over 40% cost more than US$5 million, compared to approximately 20% of moderately virtual projects.

Impact of Virtual Team Typologies on Project Success

This section of the report analyzes the typologies identified by the research to explore their impact on performance. Traditionally, project success is measured based on achievement of the triple constraints of project management: schedule, budget, and quality/performance objectives. An additional fourth constraint, meeting client expectations, is often included (Jugdev & Muller, 2005).

  Virtually Challenged Virtually Enhanced Pearson Chi-Squared
Test for Difference
Moderately Virtual Highly Virtual Pearson Chi-Squared
Test for Difference
Completed on schedule 2.86 3.73 0.000** 3.4 3.44 0.665
Completed within budget 2.84 3.72 0.000** 3.52 3.44 0.873
Achieved quality and performance objectives 3.08 4.14 0.000** 3.72 3.97 0.196
Deliverables met client expectations 3.3 4.08 0.000** 3.82 4 0.554

Table 21: Impact on project success.

The survey used four questions to assess project success, based on the project management triple constraints. The responders to the survey were asked to respond to the following statements on success of the project, using a five-point Likert scale, where 1=strongly disagree and 5=strongly agree.

The project was completed on schedule

The project was completed within or on budget

The project achieved its quality and performance objectives

The project deliverables met client expectations

Table 21 shows the mean scores for the questions, for the four typologies, and for the Pearson chi-squared test for difference between virtually challenged and virtually enhanced groups and between moderately virtual and highly virtual groups.

In summary, the empirical findings show that:

There is a significant difference in the performance of virtually enhanced teams compared to virtually challenged teams, but there is no significant difference between the performance of highly virtual teams and moderately virtual teams.

Virtually enhanced teams have the best project success rate and virtually challenged teams have the worst project success rate. The project success rates of both moderately virtual and highly virtual teams lies between challenged and enhanced teams, but there is no difference between the project success rates of highly and moderately virtual teams.

Discussion

The purpose of this research is to study the typology of virtual project teams and the implications of such a typology on project success. To that end, this paper makes three useful contributions.

First, it provides a clear, practitioner-based definition of virtuality. Virtual teams that have more than four team locations and a time difference of more than six hours between locations are classified as highly virtual, while those with fewer than four team locations and a time difference of less than six hours are moderately virtual. Teams in between these two extremes can be simply classified as virtual. While earlier researchers have used various definitions of team virtuality (Bell & Kozlowski, 2002; Fiol & O’Connor, 2005; Griffith & Neal, 2001), none have produced a simple, easy-to-operationalize measure. An additional advantage of this approach is that it is consistent with more recent research (Schweitzer & Duxbury, 2010).

The second contribution is the identification (based on a set of team characteristics) of virtually challenged and virtually enhanced teams. Table 22 details the classification of virtually challenged and virtually enhanced teams. These characteristics have a sound theoretical basis, having been developed from a detailed review of existing literature on virtual teams. But more importantly, they have been validated against a large sample of international firms from a range of sectors and disciplines. What is particularly interesting about this list of characteristics is that, with the exception of an increased emphasis on culture and possibly on aligned processes, they could be describing success characteristics of any team. In other words, the traits and characteristics of a successful team apply whether the team is virtual or not.

This point is enforced by the third contribution of this paper, the impact of physical virtuality and team characteristics on project success. A surprising finding is that virtuality does not have a significant impact on team performance. This is at odds with earlier research (Griffith & Neale, 2001; Chudoba et al., 2003), but may be a reflection of today’s working practices, in which the use of communication technology is now the norm for all teams, whether colocated or virtual; thus, the impact of virtuality is reduced.

While physical virtuality does not have an impact on success, the characteristics of the virtually enhanced teams are significantly linked with project success across all four measures. This provides a very clear template for how virtual teams need to be set up if they are to deliver successful projects. It is also interesting that the “softer” characteristics (e.g., status, vision, and experience), have a much greater impact on project success than the “harder” physical characteristics of geographic and temporal dispersion.

Characteristic Virtually Challenged Classification Virtually Enhanced Classification
Dedicated teams Low number of dedicated team members High number of dedicated team members
Virtual team experience Team members have little virtual team experience and have little experience of working with other team members. Team members have plenty of virtual team experience and have plenty of experience of working with other team members.
Team leader status The team leader or project manager is not well known, has little recognition, and interacts little within the team and the organization. The team leader or project manager is very well known, has plenty of recognition, and interacts very well within the team and the organization.
Team status The team has a poor reputation within the organization and is given the freedom to run the project as it wishes. The team has a strong reputation within the organization and is not given the freedom to run the project as it wishes.
Team vision and goals The team has poorly defined vision, goals, and objectives, and team members are poorly aligned to them. The team has strongly defined vision, goals, and objectives, and team members are strongly aligned to them.
Expertise and knowledge Team members’ expertise and knowledge are not considered much more important than job title or position, and team members are not encouraged to actively share their knowledge with the rest of the team. Team members’ expertise and knowledge are considered much more important than job title or position, and team members are strongly encouraged to actively share their knowledge with the rest of the team.
Common processes The team has more than one set of organizational policies, methodologies, and processes. The team has one set of organizational policies, methodologies, and processes.
Cultural awareness The team members are not good at recognizing the different cultural situations that arise within the team and do not understand the different economic, social, and legal conditions of the various countries in which the other team members lived. The team members are good at recognizing the different cultural situations that arise within the team and understand the different economic, social, and legal conditions of the various countries in which the other team members lived.
Cultural adaptiveness Team members do not work hard to adapt to the different cultural situations that occur within the team, are insensitive to other team members’ cultural behaviors, and this is not reflected in the way team members communicate and interact within the team. Team members work hard to adapt to the different cultural situations that occur within the team, are sensitive to other team members’ cultural behaviors, and this is reflected in the way team members communicate and interact within the team.

Table 22: Virtually challenged/enhanced classification.

Conclusion

This report has detailed an international study of more than 500 virtual teams from both large and small organizations operating in a range of sectors and disciplines. The projects that are being managed by virtual teams range from costing less than US$300,000 to more than US$10 million, and their durations range from less than three months to over two years. This research shows that virtual teams have been adopted globally as a standard way of managing projects.

The study has produced an easy-to-use measure of project virtuality that is supported by both existing research and practicing project managers. It has also shown that virtuality does not have an impact on project success. The most useful result of this study is a set of virtual project team characteristics that are significantly linked with project success.

These findings have implications for project managers of virtual project teams, and the four typologies defined will assist project managers in adopting approaches to effectively manage the different types of virtual teams. Key factors that project managers must take into consideration are:

There is little difference between virtually challenged and virtually enhanced teams with regard to team structure, project operation processes, and use of communication technology. Therefore, project managers should not concern themselves with trying to manage these aspects of virtual teams differently when working on virtually challenged teams and virtually enhanced teams.

While moderately virtual teams and highly virtual teams differ in team structure and team operation processes, there is no difference in the impact temporal dispersion has on executing tasks in parallel, building functional working relationships, understanding different physiological and social norms, and meeting task deadlines. Thus, project managers should not assume that moderately virtual teams will be less impacted by temporal dispersion than highly virtual teams.

There is a significant difference between virtually challenged and virtually enhanced teams regarding the impact of temporal dispersion. For virtually challenged teams, temporal dispersion has a negative impact on:

The ability to perform tasks in parallel

Communication among team members

The functional working relationships between team members

The understanding of team members on the different physiological and social norms or habits of team members

Achieving task deadlines

Virtually enhanced teams with dedicated team leaders, experienced team members with high levels of expertise and knowledge, a high status within the firm, strong and clear visions and goals, a common set of processes, and an awareness and willingness to adapt to cultural differences are significantly more likely to deliver successful projects.

It is useful for managers to know that teams with higher levels of physical virtuality are as likely to be successful as those with only moderate levels of physical virtuality. The soft team characteristics are more important than physical virtuality for team performance.

For researchers, this study addresses some of the limitations of previous research (Martin et al., 2004; Nader et al., 2009; Powell et al., 2006) by providing a better understanding of how virtual teams operate and the patterns and practices that they must adopt in order to perform effectively. The measure of virtuality developed can be adopted in future work to improve consistency between studies. The characteristics of enhanced virtual teams can also be built on to deepen our understanding of how project team characteristics have an impact on successful outcomes. Finally, the demographic data suggests that the use of virtual teams is ubiquitous; this is a topic that would benefit from further research.

Future research on this topic could focus on some of the issues omitted from this paper. For example, the impact of communications technology on virtual team performance, or the impact of project complexity on the success of virtual project teams.

Appendix

Publications in Virtual Project Teams by Research Method and Topic

Methodology Topic
Case Study Communication (Han, Hiltz, Fjermestad, & Wang, 2011; Bjørn & Ngwenyama, 2009; Watson-Manheim & Belanger, 2002); Conflict (Martinez-Moreno, Zornova, González-Navarro, & Thompson, 2012); Culture (Cheng, Chua, Morris, & Lee, 2012); Leadership (Domschke, Bog, Uflacker, & Zeier, 2009; Monalisa, Daim, Mirani, Dash, Khamis, & Bhusari, 2008; Kerber & Buono, 2004); Project Management (Casey & Richardson, 2006); Research Design (Steinfield, Huysman, & David, 2001); Shared Mental Model (Espinosa, Kraut, Slaughter, Lerch, Herbsleb, & Mockus, 2002); Team Design (Staples & Cameron, 2005); Team Effectiveness (Kimble, Li, & Barlow, 2000; Jarman, 2005); Team Interaction (Lee-Kelley, Crossman, & Canning, 2004); Team Life Cycle (Furst, Reeves, Rosen, & Blackburn, 2004); Technology (Scialdone, Li, Howison, Crowston, & Heckman, 2008); Traditional vs. Virtual (Powell, Galvin, & Piccoli, 2006); Trust (Crisp & Jarvenpaa, 2013) Value Creation (Lee-Kelley & Sankey, 2008; Coppola, Hiltz, & Rotter, 2004); Virtual Concepts (Kuruppuarachchi, 2009)
Experiment Communication (Pantelli & Davison, 2005; Sarker, Ahuja, Sarker, & Kirkeby, 2011; Qureshi, Liu, & Vogel, 2006; Lowry, Roberts, Romano, Cheney, & Hightower, 2006; Anderson, McEwan, Bal, & Carletta, 2007; Rico & Cohen, 2005; Altschuller & Benbunan-Fich 2010); Conflict (Furumo, 2009; Pazos, 2012); Culture (Staples & Zhao, 2006; Humes & Reilly, 2008; Paul & Ray, 2009; Gevers & Peeters, 2008; Mockaitis, Rose, & Zettinig, 2012); Dispersion (Rutkowski, Saunders, Vogel, & van Genuchten, 2007; Sarker & Sahay, 2002; Espinosa, Nan, & Carmel, 2007; Martins & Shalley, 2011; Massey, Montoya-Weiss, & Hung, 2003); Knowledge Sharing (Kanawattanachai & Yoo, 2007; Quigley, Tesluk, Locke, & Bartol, 2007); Leadership (Ocker, Huang, Benbunan-Fich, & Hiltz, 2011; Huang, Kahai, & Jestice, 2010; Carte, Chidambaram, & Becker, 2006; Sarker, Sarker, & Schneider, 2009; Purvanova & Bono, 2009); Project Success (Kayworth & Leidner, 2000; Ruggieri, 2009); Team Structure (O'Leary & Mortensen, 2010); Team Effectiveness (Edwards & Sridhar, 2003; Lin, Standing, & Liu, 2008); Team Interaction (González-Navarro, Orengo, Zornoza, Ripoll, & Peiró, 2010); Team Membership (Turel & Zhang, 2010); Traditional vs. Virtual (Stevenson & McGrath, 2004); Trust (Krebs, Hobman, & Bordia, 2006; Lowry, Zhang, Zhou, & Fu, 2010; Penarroja, Orengo, Zornoza, & Hernandez, 2013); Work Processes (Caballer, Gracia, & Peiró, 2005); Diversity (Martins & Shalley, 2011; Garrison, Wakefield, Xu, & Kim, 2010); Social Loafing (Alnuaimi, Robert, & Maruping, 2010); Technology (Turel & Connelly, 2012)
Field Study Culture (Hung & Nguyen, 2008); Diversity and Conflict (Jehn, Northcraft, & Neale, 1999); Knowledge Sharing (Espinosa, Kraut, Slaughter, Lerch, & Herbsleb, 2007); Team Challenges (Espinosa, DeLone, & Lee, 2006); Team Effectiveness (Orlikowski, 2002; Workman, 2007); Team Empowerment (Kirkman, Rosen, Gibson, Tesluk, & McPherson, 2002); Leadership (Goh & Wasko, 2012)
Interviews (Qualitative Data) Best Practices (Staples & Webster, 2007); Team Challenges (Hughes, O'Brien, Randall, Rouncefield, & Tolmie, 2001; Kirkman, Rosen, Gibson, Tesluk, & McPherson, 2002; (Dube & Robey, 2008); Communication (Belanger & Watson-Manheim, 2006; Daim, Ha, Reutiman, Hughes, Pathak, Bynum, & Bhatla, 2012); Culture (Au & Marks, 2012; Matveev & Milter, 2004; Gregory, Prifling, & Beck, 2009; Begley & Boyd, 2003; Chang, Chuang, & Chao, 2011; Dekker, Rutte, & Van den Berg, 2008); Dispersion (Espinosa & Pickering, 2006); Face-to-Face Meetings (Crowston, Howison, Masango, & Eseryel, 2007); Knowledge Sharing (Klitmoller & Lauring, 2013; Cramton, 2001); Leadership (Sivunen, 2006); Project Success (Verburg, Bosch-Sijtsema, & Vartiainen, 2013); Team Functioning (Earley & Mosakowski, 2000); Team Structure (Bal & Gundry, 1999; Gassman & von Zedtwitz, 2003; Birnholtz, Dixon, & Hancock, 2012; Dube & Pare, 2001; Dixon & Pantelli, 2010; Dube, Bourhis, & Jacob, 2006); Technology (Thomas & Bostrom, 2010); Team Development (Sarker & Sahay, 2003)
Survey Quantitative Communication (Timmerman & Scott, 2006; Majchrzak, Malhotra, & John, 2005; Glikson & Erez, 2013; Henderson, 2008); Coopetition (Lin, Wang, Tsai, & Hsu, 2010; Baruch & Lin, 2012); Culture (Workman, 2005; Kirkman, Chen, Farh, Chen, & Lowe, 2009); Dispersion (Mohammed & Nadkarni, 2011; Cummings, Espinosa, & Pickering, 2009; Curlee, 2008; Holahan, Mooney, & Finnerty Paul, 2011; Hoegl, Ernst, & Proserpio, 2007; Cummings & Hass, 2012; O'Leary & Cummings, 2002); Diversity and Conflict (Hope Pelled, Eisenhardt, & Xin, 1999; Wakefield, Leidner, & Garrison, 2008); Knowledge Sharing (Reich, Gemino, & Sauer, 2012; Chiu, Hsu, & Wang, 2006; Griffith & Sawyer, 2006; Suh & Shin, 2010; Pinjani & Palvia, 2013); Leadership (Siebdrat, Hoegl, & Ernst, 2009; Robert, 2013; Hoch & Kozlowski, 2014; Rapp, Aherne, Maithieu, & Rapp, 2010; Joshi, Lazarova, & Liao, 2009; Strang, 2011); Measuring Virtuality (Chudoba, Wynn, Lu, & Watson-Manheim, 2005; Schweitzer & Duxbury, 2010); Project Success (Lurey & Raisinghani, 2001); Social Networks (Suh, Shin, Ahuja, & Kim, 2011); Task Technology Fit (Aiken, Wang, & Gu, 2013); Team Challenges (Mihhailova, Oun, & Turk, 2009; Horwitz, Bravington, & Silvis, 2006); Team Effectiveness and Performance (Maynard, Mathieu, Rapp, & Gilson, 2012; Hardin, Fuller, & Valacich, 2006; Algesheimer, Dholakia, & Gurau, 2011; Anantatmula & Thomas, 2010; Chinowsky & Rojas, 2003); Teams—New Product Development (McDonough, Kahn, & Barczak, 2001); Traditional vs. Virtual (Webster & Wong, 2008); Trust (Brahm & Kunze, 2012; Peters & Karren, 2009; Bierly, Stark, & Kessler, 2009); Team Membership (Luse, McElroy, Townsend, & De Marie, 2013); Decision Making (Bourgault, Drouin, & Hamel, 2008); Extra-Role Performance (Ganesh & Gupta, 2010); Technology (Kock & Lynn, 2012); Online Learning (Lin, Chiu, Joe, & Tsai, 2010); Team Efficacy (Schepers, de Jong, de Ruyter, & Wetzels, 2011)
Combined (Quantitative Survey and Qualitative Interviews) Best Practice (Chen & Messner, 2010); Team Performance (Ahuja, 2010); Dispersion (McKinney & Whiteside, 2006); Cramton & Webber, 2005) Leadership (Lee–Kelley, 2006); Team Challenges (Vakola & Wilson, 2004); Team Virtuality (Gibson & Gibbs, 2006); Trust (Henttonen & Blomqvist, 2005)

References

A

Ahuja, J. (2010). A study of virtuality impact on team performance. The IUP Journal of Management Research, 9(5), 27–56.

Aiken, M., Wang, J., & Gu, L. (2013). Task knowledge and task-technology fit in a virtual team. International Journal of Management, 30(1), 3–11.

Algesheimer, R., Dholakia, U., & Gurau, C. (2011). Virtual team performance in a highly competitive environment. Group Organization Management, 36(2), 161–190.

Alnuaimi, O. A., Robert, L. P., & Maruping, L. M. (2010). Team size, dispersion, and social loafing in technology supported teams: A perspective on the theory of moral disengagement. Journal of Management Information Systems, 27, 203–230.

Altschuller, S., & Benbunan-Fich, R. (2010). Trust, performance and the communication process in ad hoc decision-making virtual teams. Journal of Computer Mediated Communication, 16, 27–47.

Anantatmula, V., & Thomas, M. (2010). Managing global projects: A structured approach for better performance. Project Management Journal, 41(2), 60–72.

Anderson, A. H., McEwan, R., Bal, J., & Carletta, J. (2007). Virtual team meetings: An analysis of communication and context. Computers in Human Behaviour, 23, 2558–2580.

Au, Y., & Marks, A. (2012). Virtual teams are literally and metaphorically invisible: Forging identity in culturally diverse virtual teams. Employee Relations, 34, 271–287.

B

Badrinarayanan, V., & Arnett, D. B. (2008). Effective virtual new product development teams: An integrated framework. Journal of Business & Industrial Marketing, 23(4), 242–248.

Bal, J., & Gundy, J. (1999). Virtual teaming in the automotive supply chain. Team Performance Management, 5(6), 174–193.

Bal. J., & Teo, P. K. (2000). Implementing virtual team working. Part 1: A literature review of best practice. Logistic Information Management, 13(6), 346–352.

Baruch, Y., & Lin, C. (2012). All for one, one for all: Coopetition and Virtual Team Performance. Technological Forecasting & Social Change, 79, 1155–1168.

Begley, T. M., & Boyd, D. P. (2003). Why don’t they like us overseas?: Organizing U.S. business practices to manage culture clash. Organisational Dynamics, 32(4), 357–371.

Belanger, F., & Watson-Manheim, M. B. (2006). Virtual teams and multiple media: Structuring media use to attain strategic goals. Group Decision and Negotiation, 15, 299–321.

Bell, B. S., & Kozlowski, S. W. J. (2002). A typology of virtual teams: Implications for effective leadership. Group and Organization Management, 27(1), 14–49.

Berry, G. (2011). Enhancing effectiveness on virtual teams: Understanding why traditional teams’ skills are insufficient. Journal of Business Communication, 48(2), 186–206.

Bierly, P. E., Stark, E. M., & Kessler, E. H. (2009). The moderating effects of virtuality on the antecedents and outcome of NPD team trust. Journal of Product Innovation Management, 26, 551–565.

Birnholtz, J., Dixon, G., & Hancock, J. (2012). Distance, ambiguity and appropriation: Structure affording impression management in a co-located organization. Computers in Human Behaviour, 28, 1028–1035.

Bjørn, P., & Ngwenyama, O. (2009). Virtual team collaboration: Building shared meaning, resolving breakdowns and creating translucence. Information Systems Journal, 19, 227–253.

Bourgault, M., Drouin, N., & Hamel, É. (2008). Decision making within distributed project teams: An exploration of formalization and autonomy as determinants of success. Project Management Journal, 39, S97–S110.

Brahm, T., & Kunze, F. (2012). The role of trust climate in virtual teams. Journal of Managerial Psychology. 27(6), 595–614.

C

Caballer, A., Gracia, F., & Peiró, J. (2005). Affective responses to work process and outcomes in virtual teams: Effects of communication media and time pressure. Journal of Management Psychology, 20, 245–260.

Carte, T., Chidambaram, L., & Becker, A. (2006). Emergent leadership in self-managed virtual teams. Group Decision and Negotiation, 15, 323–343.

Casey, V., & Richardson, I. (2006). Project management within virtual software teams. IEEE International Conference on Global Software Engineering (ICGSE 2006), Florianapolis, Brazil, October 2006, 33–42.

Chang, H., Chuang, S., & Chao, S. (2011). Determinants of cultural adaptation, communication quality and trust in virtual teams’ performance. Total Quality Management, 22(3), 305–329.

Chen, C., & Messner, J. (2010). A recommended practices system for a global virtual engineering team. Architectural Engineering and Design Management, 6, 207–221.

Cheng, C., Chua, R., Morris, M., & Lee, L. (2012). Finding the right mix: How the composition of self-managing multicultural teams’ cultural value orientation influences performance over time. Journal of Organisational Behaviour, 33, 389–411.

Chinowsky, P., & Rojas, E. (2003). Virtual teams: Guide to successful implementation. Journal of Management in Engineering, 19(3), 98–106.

Chiu, C., Hsu, M., & Wang, E. (2006). Understanding knowledge sharing in virtual communities: An integration of social capital and social cognitive theories. Decision Support Systems, 42, 1872–1888.

Chudoba, K. M., Wynn, E., Lu, M., & Watson-Manheim, M. B. (2005). How virtual are we? Measuring virtuality and understanding its impacts in a global organisation. Information Systems Journal, 15(4), 279–306.

Connaughton, S. L., & Shuffler, M. (2007). Multinational and multicultural distributed teams: A review and future agenda. Small Group Research, 38, 387.

Coppola, N. W., Hiltz, S. R., Rotter, N. G. (2004). Building trust in virtual teams. IEEE Transactions on Professional Communication, 47, 95–104.

Cramton, C. (2001). The mutual knowledge problem and its consequences for dispersed collaboration. Organisation Science, 12(3), 346–371.

Cramton, C., & Webber, S. (2005). Relationships among geographic dispersion, team processes and effectiveness in software development work teams. Journal of Business Research, 58(6), 758–765.

Crisp, C., & Jarvenpaa, S. (2013). Swift trust in global virtual teams. Journal of Personnel Psychology, 12(1), 45–56.

Crowston, K., Howison, J., Masango, C., & Eseryel, U. (2007). The role of face to face meetings in technology supported self-organizing distributed teams. IEEE Transactions of professional communication, 50(3), 185–203.

Cummings, J., Espinosa, A., & Pickering, C. (2009). Crossing spatial and temporal boundaries in globally distributed projects: A relational model of coordination delay. Information Systems Research, 20(3), 420–439.

Cummings, J., & Haas, M. (2012). So many teams, so little time: Time allocation matter in geographically dispersed teams. Journal of Organisational Behavior, 33, 316–341.

Curlee, W. (2008). Modern virtual project management: The effects of a centralized and decentralized project management office. Project Management Journal, 39, Supplement S83–S96.

D

Daim, T., Ha, A., Reutiman, S., Hughes, B., Pathak, U., Bynum, W., & Bhatla, A. (2012). Exploring the communication breakdown in global virtual teams. International Journal of Project Management, 30, 199–212.

Davidow, W. H., & Malone, M. S. (1992). The virtual corporation. New York, NY: Harper Business.

Dekker, D. M., Rutte, C. G., & Van den Berg, P. T. (2008). Cultural differences in the perception of critical interaction behaviors in global virtual teams. International Journal of Intercultural Relations, 32, 441–452.

Dixon, K. R., & Pantelli, N. (2010). From virtual teams to virtuality in teams. Human Relations, 63(8), 1177–1197.

Domchke, M., Bog, A., Uflacker, M., & Zeier, A. (2009, October). Managing globally distributes engineering teams: A case study on virtual industrial engineering. Industrial Engineering and Engineering Management, 2009, 16th International Conference, Beijing, China.

Dube, L., Bourhis, A., & Jacob, R. (2006). Towards a typology of virtual communities of practice. Interdisciplinary Journal of Information, Knowledge, and Management, 1, 69–93.

Dube, L., & Pare, G. (2001). Global virtual team. Communication of the ACM, 44(12), 71–73

Dube, L., & Robey, R. (2008). Surviving the paradoxes of virtual teamwork. Information Systems Journal, 19, 3–30.

Duranti, C. M., & de Almeida, F. C. (2012). Is more technology better for communication in international virtual teams? International Journal of e-Collaboration, 8, 36–52.

E

Earley, P. C., & Mosakowski, E. (2000). Creating hybrid team cultures: An empirical test of transactions team functioning. Academy of Management Journal, 43(1), 26–49.

Edwards, H., & Sridhar, V. (2003, January). Analysis of the effectiveness of global virtual teams in software engineering projects, 36th Hawaii International Conference on System Sciences (HICSS’03), Hawaii.

Espinosa, J. A., DeLone, W., & Lee, G. (2006). Global boundaries, task processes, and IS project success: A field study. Information Technology & People, 19(4), 345–370.

Espinosa, J., Kraut, R. E., Slaughter, S. A., Lerch, J., Herbsleb, J. D., & Mockus, A. (2002, December). Shared mental models, familiarity, and coordination: A multi-method study of distributed software teams. The 23rd International Conference on Information Systems, Barcelona, Spain.

Espinosa, J., Nan, N., & Carmel, E. (2007, August). Does gradation of time zone separation make a difference in performance? A first laboratory study. International Conference on Global Software Engineering, Munich, Germany.

Espinosa, J. A., & Pickering, C. (2006, January). The effects of time separation on coordination processes and outcomes: A case study. 39th Hawaii International Conference on Systems Sciences, Hawaii.

Espinosa, J. A., Slaughter, S. A., Kraut, R. E., & Herbsleb, J. D. (2007). Team knowledge and coordination in geographically distributed software development. Journal of Management Information Systems, 24(1), 135–169.

F

Fiol, C. M., & O’Connor, E. J. (2005). Identification in face-to-face, hybrid, and pure virtual teams: Untangling the contradictions. Organization Science, 16(1), 19–32.

Fulk, G., & DeSanctis, G. (1995). Electronic communication and changing organizational forms. Organization Science, 6(4), 337–349.

Furst, S. A., Reeves, M., Rosen, B., & Blackburn, R. S. (2004). Managing the life cycle of virtual teams. Academy of Management Executive, 18(2), 6–20.

Furumo, K. (2009). The impact of conflict and conflict management style on deadbeats and deserters in virtual teams. Journal of Computer Information Systems, 49, 66–73.

G

Ganesh, M. P., & Gupta, M. (2010). Impact of virtualness and task dependence on extra role performance in software development teams. Team Performance Management, 16, 169–186.

Garrison, G., Wakefield, R. L., Xu, X. B., & Kim, S. H. (2010). Globally distributed teams: The effect of diversity on trust, cohesion, and individual performance. Databases for Advances in Information Systems, 41, 27–48.

Gassmann, O., & von Zedtwitz, M. (2003). Trends and determinants of managing virtual R&D teams. R&D Management, 33, 243–262.

Geber, B. (1995, April). Virtual teams. Training, 32, 36–40.

Gevers, J., & Peeters, M. (2009). A pleasure working together? The effects of dissimilarity in team member conscientiousness on team temporal process and individual satisfaction. Journal of Organizational Behavior, 30(3), 379–400.

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.

Gilson, L., Maynard, M. T., Jones Young, N. C., Vartiainen, M., & Hakonen, M. A. (2015). Virtual teams research: 10 years, 10 themes, and 10 opportunities. Journal of Management, 41(5), 1313–1337.

Glikson, E., & Erez, M. (2013). Emotion display norms in virtual teams. Journal of Personnel Psychology, 12(1), 22–32.

Goh, S., & Wasko, M. (2012). The effects of leader-member exchange on member performance in virtual work teams. Journal of the Association for Information Systems, 13, 861–885.

González-Navarro, P., Orengo, V., Zornoza, A., Ripoll, P., & Peiró, J. M. (2010). Group interaction styles in a virtual context: The effects on group outcomes. Computers in Human Behaviour, 31, 1472–1480.

Gratton, L, & Erickson, T. J. (2007). Ways to build collaborative teams. Harvard Business Review, 85(3), 104–112.

Gregory, R., Prifling, M., & Beck, R. (2009). The role of cultural intelligence for the emergence of negotiated culture in IT offshore outsourcing projects. Information Technology & People, 22(3), 223–241.

Griffith, T. L., & Neale, M. A. (2001). Information processing in traditional, hybrid, and virtual teams: From nascent knowledge to transactive memory. Research in Organizational Behavior, 23, 379–421.

Griffith, T. L., & Sawyer, J. E. (2006). Supporting technologies and organisational practices for the transfer of knowledge in virtual environments. Group Decision and Negotiation, 15, 407–423.

H

Han, H., Hiltz, S., Fjermstad, J., & Wang, Y. (2011). Does medium matter? A comparison of initial meeting modes for virtual teams, IEEE Transactions on Professional Communication, 54, 376–391.

Hardin, A., Fuller, M., & Valacich, J. (2006). Measuring group efficacy in virtual teams: New questions in an old debate. Small Group Research, 37(1), 65–85.

Henderson, L. S. (2008). The impact of project managers’ communication competencies: Validation and extension of a research model of virtuality, satisfaction, and productivity on project teams. Project Management Journal, 39, 48–59.

Henry, J. E., & Hartzler, M. (1997). Virtual teams: Today’s reality, today’s challenge. Quality Progress, 30, 108–109.

Henttonen, K., & Blomqvist, K., (2005). Managing distance in a global virtual team: The evolution of trust through technology-mediated relational communication. Strategic Change, 14, 107–119.

Hoch, J. E., & Kozlowski, S. W. (2014), Leading virtual teams: Hierarchical leadership, structural supports, and shared team leadership. Journal of Applied Psychology, 99, 390–403.

Hoegl, M., Ernst, H., & Proserpio, L. (2007). How teamwork matters more as team member dispersion increases, Journal of Product Innovation Management, 24(2), 156–165.

Holahan, P., Mooney, A., & Finnerty Paul, L. (2011). Moderating effects of geographic dispersion and team tenure on the task-affective conflict relationship. Current Topics in Management, 15, 41–62.

Hope Pelled, L., Eisenhardt, K., & Xin, K. (1999). Exploring the black box: An analysis of work group diversity, conflict, and performance. Administrative Science Quarterly, 44(1), 1–28.

Hosseni, M., Zuo, J., Chileshe, N., & Baroudi, B. (2013). A conceptual meta-framework for managing multicultural global virtual teams. International Journal of Networking and Virtual organisations, 12(4), 310–330.

Howitz, F. M., Bravington, D., & Silvis, U. (2006). The promise of virtual teams: Identifying key factors in effectiveness and failure. Journal of European Industrial Training, 30, 472–494.

Huang, R‥, Kahai, S., & Jestice, R. (2010). The contingent effects of leadership on team collaboration in virtual teams. Computers in Human Behaviour, 26, 1098–1110.

Hughes, J., O’Brien, J., Randall, Rouncefield, M., & Tolmie, P. (2001). Some ‘real’ problems of ‘virtual’ organizations. New Technology, Work and Employment, 16(1), 49–65.

Humes, M., & Reilly, A., (2008). Managing intercultural teams: The organization exercise. Journal of Management Education, 32(1), 118–137.

Hung, Y., & Nguyen, M. (2008, January). The impact of cultural diversity on global virtual team collaboration—A social identity perspective. 41st Hawaii International Conference on System Sciences, Hawaii.

J

Jarman, R. (2005). When success isn’t everything—Case studies of two virtual teams. Group Decision and Negotiation, 14, 333–354.

Jehn, K., Northcraft, G., & Neale, M. (1999). Why differences make a difference: A field study of diversity, conflict and performance in work groups. Administrative Science Quarterly, 44(40) 741–763.

Johnson, P., Heimann, V., & O’Neill, K. (2001). The ‘Wonderland’ of virtual teams. Journal of Workplace Learning, 13(1), 24–30

Joshi, A., Lazarova, M. B., & Liao, H.,2009). Getting everyone on board: The role of inspirational leadership in geographically dispersed teams. Organization Science, 20, 240–252.

Jugdev, K., & Muller, R. (2005). A retrospective look at our evolving understanding of project success. Project Management Journal, 36(4), 19–31.

K

Kanawattanachai, P., & Yoo, Y. (2007). The impact of knowledge coordination on virtual team performance over time. MIS Quarterly, 31(4), 783–808.

Kayworth, T., & Leidner, D. (2000). The global virtual manager: A prescription for success. European Management Journal, 18(2), 183–194.

Kerber, K., & Buono, A. (2004). Leadership challenges in global virtual teams: Lessons from the field. SAM Advanced Management Journal, Autumn, 2004.

Kimble, C., Li, F., & Barlow, A. (2000). Effective virtual teams through communities of practice. Management Science Theory, Method, and Practice, Strathclyde Business School, Research Paper 2000/9.

Kirkman, B. L., Chen, G., Farh, J., Chen, Z., & Lowe, K. (2009). Individual power distance orientation and follower reactions to transformational leaders: A cross-level, cross-cultural examination. Academy of Management Journal, 52(4), 744–764.

Kirkman, B. L., Rosen, B., Gibson, C., Tesluk, P., & McPherson, S. (2002). Five challenges to virtual team success: Lessons from Sabre, Inc. Academy of Management Executive, 16(3), 67–79.

Klitmoller, A., & Lauring, L. (2013). When global virtual teams share knowledge: Media richness, cultural difference, and language commonality. Journal of World Business, 48, 398–406.

Kock, N., & Lynn, G. S. (2012). Electronic media variety and virtual team performance: The mediating role of task complexity coping mechanisms. IEEE Transactions on Professional Communication, 55, 325–344.

Krebs, S., Hobman, E., & Bordia, P. (2006). Virtual teams and group member dissimilarity: Consequences for the development of trust. Small Group Research, 37, 721.

Krumm, S., Terwiel, K., & Hertel, G. (2013). Challenges in norm formation and adherence: The knowledge, skills, and ability requirements of virtual and traditional cross-cultural teams. Journal of Personnel Psychology, 12(1), 33–44.

Kuruppuarachchi, P. R. (2009). Virtual team concepts on projects: A case study. Project Management Journal, 40(2), 19–33.

L

Lee-Kelley, L. (2002). Situational leadership: Managing the virtual project team. Journal of Management Development, 21(6), 461–476.

Lee-Kelley, L. (2006). Locus of control and attitudes to working in virtual teams. International Journal of Project Management, 24, 234–243.

Lee-Kelley, L., Crossman, A., & Canning, A. (2004). A social interaction approach to managing the “invisibles” of virtual teams. Industrial Management & Data Systems, 104(8), 650–657.

Lee-Kelley, L., & Sankey, T. (2008). Global virtual teams for value creation and project success: A case study. International Journal of Project Management, 26, 51–62.

Lin, C., Chiu, C., Joe, S., & Tsai, Y. (2010). Assessing online learning ability from a social exchange perspective: A survey of virtual teams with business organisations. International Journal of Human Computer Interaction, 26, 849–867.

Lin, C., Standing, C., & Liu, Y. (2008). A model to develop effective virtual teams. Decision Support Systems, 45, 1031–1045.

Lin, C., Wang, Y., Tsai, Y., & Hsu, Y. (2010). Perceived job effectiveness in coopetition: A survey of virtual teams within business organization. Computers in Human Behaviour, 26, 1598–1606.

Lipnack, J., & Stamps, J. (2000). Virtual teams: People working across boundaries with technology (2nd ed.). New York, NY: John Wiley & Sons.

Lowry, P. B., Roberts, T. L., Romano, Jr., N. C., Cheney, P. D., & Hightower, R. T. (2006). The impact of group size and social presence on small group communication. Small Group Research, 37, 631–661.

Lowry, P. B., Zhang, D. S., Zhou, L. N., & Fu, X. L. (2010). Effect of culture, social presence, and group composition on trust in technology-supported decision making groups. Information Systems Journal, 20, 297–315.

Lurey, J., & Raisinghani, M. (2001). An empirical study of best practices in virtual teams. Information & Management, 38, 523–544.

Luse, A., McElroy, J. C., Townsend, A. M., & DeMarie, S. (2013). Personality and cognitive style as predictors of preference for working in virtual teams. Computer in Human Behaviour, 29, 1825–1832.

M

Majchrzak, A., Malhotra, A., & John, R. (2005). Perceived individual collaboration know-how development through information technology enabled contextualization: Evidence from distributed teams. Information Systems Research, 16(1), 9–27.

Marks, A., & Richards, J. (2012). Developing ideas and concepts in teamwork research: Where do we go from here? Employee Relations, 32(3), 228–234.

Martin, L. L., Gilson, L. L., & Maynard, M. T. (2004). Virtual teams: What do we know and where do we go from here? Journal of Management, 30(6), 805–835.

Martinez-Moreno, E., Zornova, A., González-Navarro, P., & Thompson, L. F., (2012). Investigating face to face and virtual teamwork over time: When does early task conflict trigger relationship conflict? Group Dynamics: Theory, Research, and Practice, 16(3), 159–171.

Martins, L., & Shalley, C. (2011). Creativity in virtual work: Effects of demographic differences. Small Group Research, 42, 536.

Massey, A., Montaya-Weiss, M., & Hung, Y. (2003). Because time matters: Temporal co-ordination in global virtual project teams. Journal of Management Information Systems, 19(4), 129–155.

Matveev, A., & Milter, R. (2004). The value of intercultural competence for performance of multicultural teams. Team Performance Management, 10(5/6), 104–111.

Maynard, M. T., Mathieu, J. E., Rapp, T. L, & Gilson, L. L. (2012). Something(s) old and something(s) new: Modeling drivers of global virtual team effectiveness. Journal of Organisational Behaviour, 33, 342–365.

McDonough, E., Kahn, K., & Barczak, G. (2001). An investigation of the use of global, virtual, and co-located new product development teams. The Journal of Product Innovation Management, 18, 110–120.

McKinney, V., & Whiteside, M. (2006, March). Maintaining distributed relationships: Electronic communication works best when it increases interaction and collaboration through a variety of media. Communications of the ACM, 49(3), 82–86.

Mihhailova, G., Oun, K., & Turk, K. (2009). Virtual work and its challenges and types, The Business Review, 12(2).

Mockaitis, A. I., Rose, E. L., & Zettinig, P. (2012). The power of individual cultural values in global virtual teams. International Journal of Cross-Cultural Management, 12, 193–210.

Mohammed, S., & Nadkarni, S. (2011). Temporal diversity and team performance: The moderating role of team temporal leadership. Academy of Management Journal, 54(3), 489–508.

Monalisa, M., Daim, T., Mirani, F., Dash, P., Khamis, R., & Bhusari, V. (2008). Managing global design teams. Research, Technology Management, 51(4), 48–59.

Moser, K., & Axtell, C. (2013). The role of norms in virtual work: A review and agenda for future research. Journal of Personnel Psychology, 12(1), 1–6.

Mukherjee, D., Lahiri, S., Mukherjee, D., & Billing, T. (2012). Leading virtual teams: How do social, cognitive, and behavioral capabilities matter? Management Decision, 50(2), 273–290.

N

Nader, A. E, Shamsuddin, A., & Zahari, T. (2009). Virtual teams: A literature review. Australian Journal of Basic and Applied Sciences, 3(3), 2653–2669.

O

Ocker, R. J., Huang, H., Benbunan-Fich, R., & Hiltz, S. R. (2011). Leadership dynamics in partially distributed teams: An exploratory study of the effects of configuration and distance. Group Decision & Negotiation, 20, 273–292.

O’Leary M., & Cummings, J. (2007). The spatial, temporal, and configurational characteristics of geographic dispersion in work teams. MIS Quarterly, 31(3), 433–452.

O’Leary, M., & Mortenson, M. (2010). Go (con)figure: Subgroups, imbalance, and isolates in geographically dispersed teams. Organisation Science, 21, 115–131.

Orlikowski, W. J. (2002). Knowing in practice: Enacting a collective capability in distributed organizing. Organization Science, 13(3), 249–273.

P

Pantelli, N., & Davison, R. M. (2005). The role of subgroups in the communication patterns of global virtual teams. IEEE Transactions on Professional Communication, 48(2), 191–200.

Paul, S., & Ray, S. (2009, January). Cultural diversity, perception or work atmosphere and task conflict in collaboration technology supported global virtual teams: Findings from a lab experiment. 42nd Hawaii International Conference on System Sciences, Hawaii.

Pazos, P. (2012). Conflict management and effectiveness in virtual teams. Team Performance Management, 18, 401–417.

Penarroja, V., Orengo, V., Zornoza, A., & Hernandez, A. (2013). The effects of virtuality level on task-related collaborative behaviour: The mediating role of team trust. Computers in Human Behaviour, 29, 967–974.

Peters, L., & Karren, R. (2009). An examination of the roles of trust and functional diversity on virtual team performance ratings. Group & Organisation Management, 34(4), 479–504.

Pinjani, P., & Palvia, P. (2013). Trust and knowledge sharing in diverse global virtual teams. Information and Management, 50, 144–153.

Pinto, J. K., & Slevin, D. P. (1988). Critical success factors in successful project management. IEEE Transactions on Engineering Management, 34(1), 22–27.

Powell, A., Galvin, J., & Piccoli, G. (2006). Antecedents to team member’s commitment from near and far: A comparison between co-located and virtual teams. Information Technology & People, 19(4), 299–322.

Purvanova, R., & Bono, J. (2009). Transformational leadership in context: Face-to-face and virtual teams. The Leadership Quarterly, 20, 343–357.

Q

Quigley, N., Tesluk, P. E., Locke, E., & Bartol (2007). A multi-level investigation of the motivational mechanisms underlying sharing and performance. Organisation Science, February.

Qureshi, S., Liu, M., & Vogel, D. (2006). The effects of electronic collaboration in distributed project management. Group Decision and Negotiation, 15, 55–75.

R

Rapp, A., Aherne, M., Mathieu, J., & Rapp, T. (2010). Managing sales teams in a virtual environment. International Journal of Research and Marketing, 27, 213–224.

Reich, B., Gemino, A., & Sauer, C. (2012). Knowledge management and project-based knowledge in IT projects: A model and preliminary empirical results. International Journal of Project Management, 30(6), 663–674.

Rico, R., & Cohen, S. G. (2005). Effects of task interdependence and type of communication on performance in virtual teams. Journal of Managerial Psychology, 20, 261–274.

Robert, L. (2013, February). A multilevel analysis of the impact of shared leadership in diverse virtual teams. Research Gate, San Antonio, TX, USA.

Ruggieri, S., (2009). Leadership in virtual teams: A comparison of transformational and transactional leaders. Social, Behaviour & Personality, 37, 1017–1022.

Rutkowski, A., Saunders, C., Vogel, D., & van Genuchten, M. (2007). Is it already 4 a.m. in your time zone? Focus immersion and temporal dissociation in virtual teams. Small Group Research, 38, 98.

S

Sarker, S., Ahuja, M., Sarker, S., & Kirkeby, S. (2011). The role of communication and trust in global virtual teams: A social network perspectives. Journal of Management Information Systems, 28(10), 273–309.

Sarker, S., & Sahay, S. (2002, January). Information systems development by US-Norwegian virtual teams: Implications of time and space. 35th Hawaii International Conference on System Sciences, Hawaii.

Sarker, S., & Sahay, S. (2003). Understanding virtual team development: An interpretive study. Journal of the Association for Information Systems, 4, 1–38.

Sarker, S., Sarker, S., & Schneider, C. (2009). Seeing Remote Team Members as Leaders: A Study of US-Scandinavian Teams. IEEE Transactions on Professional Communications, 52(1), 75–94.

Saunders, C., Van Slyke, C., & Vogel, D. R. (2004). My time or yours? Managing time visions in global virtual teams. Academy of Management Executive, 18, 19–31.

Schepers, J., de Jong, A., de Ruyter, K., & Wetzels, M. (2011). Fields of gold: Perceived efficacy in virtual teams of field service employees. Journal of Service Research, 14, 372–389.

Schlenkrich, L., & Upfold, C. (2009). A guideline for virtual team managers: The key to effective social interaction and communication. The Electronic Journal Information Systems Evaluation, 12(1), 109–118.

Schweitzer, L., & Duxbury, L. (2010). Conceptualizing and measuring the virtuality of teams. Information Systems Journal, 20, 267–295.

Scialdone, M. J., Li, N., Howison, J., Crowston, K., & Heckman, R., (2008, August). Group maintenance in technology-supported distributed teams. Academy of Management Proceedings, 1, 1–6.

Siebdrat, F., Hoegl, M., & Ernst, H. (2009). How to manage virtual teams. MIT Sloan Management Review, Summer.

Sivunen, A. (2006). Strengthening identification with the team in virtual teams: The leaders’ perspective. Group Decision and Negotiation, 15, 345–366.

Staples, D. S., & Cameron, A. F. (2005, January). The effect of task design, team characteristics, organizational context, and team processes on the performance and attitudes of virtual team members. Proceedings of the 38th Hawaii International Conference on System Sciences, Hawaii.

Staples, D. S., & Webster, J. (2007). Exploring traditional and virtual team members’ “best practices”: A social cognitive theory perspective. Small Group Research, 38(1), 60–67.

Staples D. S., & Zhao, L., (2006). The effects of cultural diversity in virtual teams versus face to face teams. Group Decision and Negotiation, 15, 389–406.

Steinfield, C., Huysman, M., & David K. (2001, January). New methods for studying global virtual teams: Towards a multifaceted approach. Proceedings from the 34th Hawaii International Conference on Systems Sciences, Hawaii.

Stevenson, W., & McGrath, E., (2004). Differences between onsite and off-site teams: Manager perceptions. Team Performance Management, 10(5/6), 127–132.

Strang, K. D., (2011). Leadership substitutes and personality impact on time and quality in virtual new product development projects. Project Management Journal, 42, 73–90.

Suh, A., & Shin, K., (2010). Exploring the effects of online social ties on knowledge sharing: A comparative analysis of co-located vs. dispersed teams. Journal of Information Science, 36, 443–463.

Suh, A., Shin, K., Ahuja, M., & Kim, M. (2011). The influence of virtuality on social networks within and across work groups: A multilevel approach. Journal of Management Information Systems, 28, 351–386.

T

Thomas, D. M., & Bostrom, R. P. (2010). Vital signs for virtual teams: An empirically adapted trigger model for technology adaption interventions. MIS Quarterly, 34(1), 115–142.

Timmerman, C., & Scott, C. (2006). Virtually working: Communicative and structural predictors of media use and key outcomes in virtual work teams. Communication Monographs, 73(1), 108–136.

Townsend, A. M., De Marie, S. M., & Hendrickson, A. R. (1998). Virtual teams: Technology and the workplace of the future. The Academy of Management Executive, 12(3), 17–19.

Turel, O., & Connelly, C., (2012). Team spirit: The influence of psychological collectivism on the usage of e-collaboration tools. Group Decision and Negotiation, 21, 703–725.

Turel, O., Zhang, Y. (2010). Does virtual team composition matter? Trait and problems solving configuration effects on team performance. Behaviour & Information Technology, 29(4), 363–375.

V

Vakola, M., & Wilson, I., (2004). The challenge of virtual organisation: Critical success factors in dealing with constant change. Team Performance Management, 10(5/6), 112–120.

Verburg, R., Bosch-Sijtsema, P., & Vartiainen, P. (2013). Getting it done: Critical success factors for project managers in virtual work settings. International Journal of Project Management, 31, 68–79.

W

Wageman, R., Gardner, H., & Mortensen, M. (2012). The changing ecology of teams: New directions for team’s research. Journal of Organisational Behavior, 33, 31–315.

Wakefield, R. L., Leidner, D. E., & Garrison, G. (2008). A model of conflict, leadership, and performance in virtual teams. Information Systems Research, 19, 434–455.

Wang, D., Waldman, D., & Zhang, Z. (2014). A meta-analysis of shared leadership and team effectiveness. Journal of Applied Psychology, 99(2), 181–198.

Watson-Manheim, M. B., & Belanger, F. (2002, January). Exploring communication-based work processes in virtual environments. Proceedings of the 35th Hawaii international conference on system sciences, Hawaii.

Watson-Manheim, M. B., Chudoba, K. M., & Crowston, K. (2002). Discontinuities and continuities: A new way to understand virtual work. Information, Technology & People, 15(3), 191–209.

Webster, J., Wong, W. K. P. (2008). Comparing traditional and virtual group forms: Identity, communication, and trust in naturally occurring project teams. The International Journal of Human Resource Management, 19(1), 41–62.

Wong, S., & Burton, R. M. (2000). Virtual teams: What are their characteristics and impact on team performance? Computational & Mathematical Organization Theory, 6, 339–360.

Workman, M. (2005). Virtual team culture and the amplification of team boundary permeability on performance. Human Resource Development Quarterly, 16(4), 435–458.

Workman, M. (2007). The proximal-virtual team continuum: A study of performance. Journal of the American society for the information science and technology, 58(6), 794–801.

Z

Zander, L., Mockaitis, A., & Butler, C. (2012). Leading global teams. Journal of World Business, 47, 592–603.

Zhang, S., Tremaine, M., Fjermstad, J., Milewski, A., & O’Sullivan, P. (2006, October). Delegation in virtual teams: The moderating effects of team maturity and team distance. IEEE International Conference on Global Software Engineering (ICGSE’06), Florianopolis, Brazil.

Contributors

Padhraic Ludden:

Padhraic Ludden is a program manager with Hewlett-Packard. He is conducting doctoral research with the Enterprise Research Centre, University of Limerick. Padhraic graduated with honors from the National University of Ireland, Galway (NUIG) in 1984 with a bachelor’s degree in industrial engineering. He has 29 years of experience in the manufacturing sector; over 25 of those years was with Hewlett-Packard. He has worked predominately as a project/program manager, providing IT application services to manufacturing companies such as GM and SKF. Between 2001 and 2003, he completed a master’s degree in project management (MPM) at the University of Limerick, gaining a first-class honors degree and winning both top student and best dissertation awards. Mr. Ludden continues to act as a tutor for the course. He has previously researched project management maturity and presented a paper on PMI’s Organizational Project Management Maturity Model (OPM3)® versus SEI-CMMI at the PMI® Global Congress 2004—EMEA. His doctoral research is on the typology of virtual project teams and his paper, A Typology Framework for Virtual Teams, was presented at the PMI® Research and Education Conference, Limerick, Ireland, 2012 and the PMI® Research and Education Conference, Portland, Oregon, United States, 2014. He is a certified Project Management Professional (PMP)® and a former president of the PMI Ireland Chapter. He completed the PMI Leadership Institute Master Class in 2008 and was the PMI Europe, Middle East, and Africa (EMEA) component mentor from 2008 to 2011. He was also a member of the PMI Chapter Member Advisory Group (CMAG) from 2011 to 2013.

Ann Ledwith, PhD:

Ann Ledwith is the director of Continuing and Professional Education at the University of Limerick (UL) in Ireland. She is also the academic director of a distance learning master’s program in technology management. She has previously held roles as the Director of the Centre for Project Management, Director of Educational Programmes at the Enterprise Research Centre, and Assistant Dean of Adult and Continuing Education for Science & Engineering. Before joining UL, she spent 12 years in industry, initially as an R&D engineer, and later, as R&D manager in a small firm developing and manufacturing automatic test equipment. Her research interests include new product development, technology management, and project management. She has published on these topics in various journals, including Journal of Product Innovation Management, International Journal of Project Management, International Journal of Product Development, Research Technology Management, Creativity and Innovation Management, and Management Decision.

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