A typology framework for virtual project teams
an empirical investigation
Engineering Research Centre University of Limerick
Ann Ledwith, PhD
Director of Continuing and Professional Education University of Limerick
In the modern work environment, the need for organizations and people to work on a global level has increased. Today, the team as a grouping of co-located people working for a common purpose is no longer the norm. Instead, people find that team work occurs across many time zones, locations, and organizations. This type of teamwork has led to the development of the term virtual team. It is therefore important that the working and functioning of virtual teams are better understood. The aim of this research is to investigate the typology of virtual teams in order to assist future researchers in studying the phenomena of virtual teams.
A review of published papers on the nature of virtual teams suggests that there are eight key areas of focus in the characteristics of virtual teams- temporal, geographic, culture, social, political, team membership, communication technology, and task complexity. From these eight characteristics, a standard set of measurable items to investigate the typology of virtual teams is developed.
The initial empirical findings from a large-scale global survey of the project management community provide a picture of the typical typology of a virtual project team. It is a global team of around 15 members across approximately four locations. The project executed by the team is complex, of duration between six months to two years, and costs less than US$5 million. The ratio between permanent organization resources and contractors is 60%:40%; and approximately 60% of the team are fully dedicated to the project and report directly to the team leader. Team members have a diversity of knowledge and skills. The primary communication tools used are email and phones. The number of organizations involved in a virtual team is normally three. However, the team only uses one set of organization methodologies, processes, and policies. There is usually one sole leader of the team with a proven track record. The team has strong reputational capital and is aligned to a common vision and goals. There is a good awareness of the cultural differences within the team and while temporal dispersion does cause task execution and communication challenges, overall performance is not impacted.
Keywords: virtual team; team typology; team characteristics; team membership
In the modern work environment, the need for organizations and people to work on a global level has increased. Today, the team as a grouping of co-located people working for a common purpose is no longer the norm. Instead, people find that team work occurs across many time zones, locations, and organisations. This type of team work 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 U.S. multinationals and their affiliates overseas began using the team concept in order to integrate their work practices. Increased globalization and the rapid improvements in communication technology have resulted in a huge growth in the use of virtual teams; with Martin, Gilson, and Maynard (2004) contending that nearly all organizational teams are virtual to some extent; and Johnson, Heimann, and O'Neill (2001) stating that we have moved away from working with people who are in visual proximity to working with people who are around the globe. It is, therefore, important that the working and functioning of virtual teams are better understood.
Published reviews of literature on virtual teams (Martin et al, 2004; Nader, Shamsuddin, & Zahari, 2009; Powell, Piccoli, & Ives, 2006) show evidence of a considerable volume of research. Martin et al. (2004) note that we are only beginning to understand how virtual teams function and that more work is required in order to facilitate the design and management of virtual teams. According to Powell et al. (2006), the majority of the literature focuses on the implications of virtual teams' inability to meet face-to-face and their reliance on electronic communication media. In the conclusion to their review, Nader et al. ( 2009) state that there is a need to provide an assessment of what patterns, practice, or types of activities a virtual team must execute in order to perform effectively.
A standard set of characteristics of virtual teams to assist in the exploration of virtual team typologies was defined by Ludden, Ledwith, and Lee-Kelley (2012). Further refinement of this standard set resulted in eight characteristics, which are used in this research to develop the survey instruments used for a large-scale investigative study of virtual team typology.
The objective of this paper is to provide empirical evidence on the typology of virtual project teams that will enable further research into the understanding of the mechanisms and challenges of working in virtual project teams. First, the eight characteristics used to explore virtual team typology are outlined – temporal, geographic, cultural, social, political, team membership, communication technology, and task complexity. The development of a survey to conduct a large-scale empirical investigation of virtual project teams is then described. The descriptive statistics from the survey are presented and the findings are discussed. These findings are the initial analysis of the survey data. Further analysis is planned to test and reduce the attribute items, determine if correlations exist between attributes, and also determine if identified clusters and patterns in virtual teams can predict project success factors.
The Characteristics of Virtual Teams
A review of published papers on the nature of virtual teams suggests that there are eight key areas of focus in the characteristics of virtual teams. This section will outline and discuss these eight areas.
It is evident that temporal and geographic distribution 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 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 proposes that the greater the complexity, the greater the need for the team to work in a real/common time zone. The influence of culture from the aspect of perception of time and the impact of time being culturally bound is also considered (Connaughton & Shuffler, 2007; Saunders, Van Slyke, & Vogel, 2004).
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 (collocated/no dispersion) against pure virtual teams (100% dispersion) (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, 2003; Foil & 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).
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, & Gwanhoo, 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.
For the social boundary, key themes are common goals and shared leadership. Orlikowski's (2002) boundary list resulted from his study of the Kappa organization. The boundaries 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 a common goal and objectives (Bal & Teo, 2000; Geber, 1995; Henry & Hartzler, 1997; Lipnack & Stamps, 2000; Nader et al, 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.
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.
Team members are a key focus in the research of virtual teams. The central themes for team membership are member skill sets, temporal nature/dynamism of the team, and multivariate aspects of the member – multi-tasking, multi-company, multi-reporting, and interdependency. There is general consensus that members of virtual teams are skilled knowledge workers (Bal & Teo, 2000; Lee- Kelley, 2002), that many teams are made of members from multiple companies, that many are contractors, and that many multi-task across teams (Chudoba et al., 2003; Lee-Kelley, 2002; Nader et al., 2007; 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). 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)
All virtual teams utilize computerized media communication. Bal and Teo (2003) view technological communications in the way it enables 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 the dependency on technology; with the greater the geographic dispersion, the greater the dependency (Gibson & Cohen, 2003; Dube et al., 2006; Zhang et al., 2006). While technology is not an attribute of Bell and Kozlowski's (2003) virtual team typology model, they state 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).
The nature of the task being conducted by the virtual team is considered important in the research literature. Task design, composition, interdependency, 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). Some authors classify the tasks performed by virtual teams as orientating from the operational to the strategic (Espinosa et al., 2006; Lee-Kelley, 2002), with Wong and Burton (2000) describing them as novel and Schlenkrich and Upfold (2009) describing them as non-routine.
This review has detailed the research on the eight characteristics used to investigate virtual teams. The next section will describe the development of the survey instrument based on these eight attributes.
The eight characteristics identified to investigate virtual team typology (Ludden et al., 2012) are now used to develop the survey instrument to study virtual teams.
For temporal dispersion, the literature shows that key elements when considering temporal dispersion are – number of time zones, differences in time zones, number of team members located/configured in each time zone, change in working norms, degree of path dependency, level of asymmetric communication, physiological and social rhythm differences, multiple time references and time adjustments, silence, and delay (Sarker & Sahay, 2002; O'Leary & Cummings, 2002; Espinosa & Pickering, 2006; Harvey & Griffith, 2007). The items used by this study to measure the level of temporal dispersion are – the number of time zones, difference in time zones, and hours worked outside normal business hours. To gauge the impact of temporal dispersion, the challenges outlined by Sarker and Sahay (2002) are used. These measure the impact of temporal dispersion on task completion, communication, and physiological and social rhythms.
O'Leary and Cummings (2002) use three indices – site, isolation, and separation to measure geographical dispersion. Espinosa and Pickering (2006) highlight the importance of distinguishing between north-south and east-west distribution. Schweitzer and Duxbury (2010) focus on three degrees of virtuality – team time worked virtually, member virtuality, and distance virtuality. Past research also uses team member distance, percentage of isolated members, and unevenness in members across sites to study geographical distribution (MacDuffie, 2007; Ghemewat, 2001). In order to measure geographical distribution for this research, the following measures are selected:
- Number of team locations.
- Were team locations within one city, one region/state, one country, one continent, one hemisphere, or two hemispheres?
- Distribution of team members across locations.
The work of Hofstede (1980), Trompenaars and Hampden-Turners (1997), and Bennet (1993) have defined the many dimensions of cross-cultural research. The literature shows that the key cultures to focus on are national, organizational, functional, and team. While this study acknowledges the valuable research in this area, the focus of this research paper is not on the various dimensions of culture, but on the manner in which the team is aware of, and adapts to, the different cultures within the virtual team. The survey instrument used first ascertains the extent of physical cultural diversity by identifying the number of different nationalities and languages spoken within the team. It then uses the Kim, Kirkman, & Chen (2006) four-factor model based on culture quotients to measure a team's awareness of, and adaption to, the various cultures that exist within a virtual team.
Hofstede (1991) argues that cultural differences at the organizational level emanate from the employees' shared perceptions of practices at the workplace. Bjorn and Ngwenyama (2009) provide a similar view with their three-level model (life-world, organization and work practice), where organizational structure comprises of the explicit, articulated, and visible structures such as policies, norms, symbolic artifacts, ritual activity, and patterned behavior. In order to assess the diversity of organizational culture within a virtual team, this research proposes to measure the actual number of organizations represented on the team and the impact of organizational policies, methodologies, and processes on a virtual team. Functional culture can be classified as the range of functional categories that exist within an organization and focuses on the different assignments within these functions. Thus, the survey measures used verify the number of different functional areas and subject matter expert areas involved in the team, and then assesses the impact of these areas by questioning how they use the team methodologies, processes, and policies.
Lipnack and Stamps (2000) state that for virtual teams, people come together with the hope that by combining effort, they can achieve something great. They also propose that position varies enormously in virtual teams, that membership has a wide diversity of knowledge and skills, and that everyone on a virtual team needs to be an expert in something the team requires. Kimball (1997) suggests that with virtual teams, leadership is shared;knowledge is pulled among team members rather than a centralized push; all members feel comfortable sharing what they know; and that some common ground needs to be created for the group. To study the social aspect of virtual teams, the survey poses questions on:
- Strength of vision, goals, and objectives.
- The extent to which leadership is shared.
- The type of authority that exists.
- The transaction of knowledge.
Harvey, Novicevic, and Garrisson (2004) studied virtual teams from the four critical human resource capitals of human, social, political, and cross-cultural. They state that the six leadership measures that influence the formation of political capital are social approximation, level/type of interaction, scope and reach, dispersion of knowledge, durability, and degree of formality. These measures are adapted by this research to study the political attributes of a virtual team. The rating scale used for both the political and social questions is a five-point Likert scale that ranges from 1 (strongly disagrees) to 5 (strongly agrees).
Past research identifies the following elements to measure and investigate membership of virtual teams – skill diversity, role, experience, reporting, familiarity, use of communication technology, and permanent vs. contractor. To assess the extent of team members' dedication to the team, dedicated roles, direct reporting, and permanence, the survey measures the responses using a six point Likert scale – 0–10% (1), 11–30% (2), 31–50% (3), 51–70% (4), 7190% (5), and 91–100% (6).
The literature on communication technology focuses primarily on the following tools – video conferencing, web conferencing, instant messaging, remote access and control, email, telephone, data sharing repositories, letter/fax, social networks, and web portals. (Nader et al., 2009; Thissen, Jean, Madhavi, & Toyia, 2007; Watson-Manheim & Belanger, 2002; Poehler & Schumacher, 2007; Domschke, Bog, Uflacker, & Zeier, 2009; Olson & Olson, 2000). In order to measure the usage of these tools, the survey adapts Webster and Wong's (2008) frequency of usage of a seven-point Likert scale to the following six-point Likert scale – 'Never' (1), 'A number of times in a 6 month period' (2), 'A number of times a month' (3), 'A number of times a week' (4), 'A number of times a day' (5), ' Almost continuously' (6).
Grattan and Erikson's (2007) seven-statement true/false task complexity test is used to measure task complexity as this adequately indicates if a task is complex. For Grattan and Erikson, a task is deemed complex if two or more statements are true. This study rates the degree of complexity as the total number of statements that are true. One of the seven statements is "the members of the team working on the task are in more than two locations". As the number of team locations is addressed elsewhere in the survey, this statement was not used in the measure of task complexity.
Demographic and Performance
The survey includes demographic questions that seek information on the task/project undertaken in regard to duration, size, and cost. The aim of asking these questions is to verify the current research view on the short term and temporal nature of virtual teams (Lipnack & Stamps 2000, Bell & Kozlowski 2002, Bal & Teo 2000, Chudoba et al. 2003, Martin et al. 2004, Powell et al. 2006). In order to improve the survey's data analysis potential, questions were also asked about details such as company type in which the team exists, industry focus in which the company is working, and size of the company (people and revenue). Survey respondents were requested to state their nationality, country of residence, education level, length of work experience, job role on the virtual team, and length of experience in the job role.
Finally, in order to measure the impact that a certain team typology has on project team performance, the survey assesses overall project performance by asking the responder to rate the performance of their virtual team project using Pinto and Slevin's (1988) four project success factors – delivered on schedule, completed on budget, achieved quality and performance objectives, and met client expectations. The rating used is a five-point Likert scale that ranges from 1 (strongly disagrees) to 5 (strongly agrees).
The above measurement items were used to develop a survey to explore virtual team typology. This survey was distributed using the Survey Monkey® tool. Next, the survey's distribution and demographic findings are described.
Survey Distribution Process and Demographic Findings
The survey was open to selected members of the Project Management Institute (PMI) over a two-month period. The method of distribution was to request chapter presidents from a selected number of PMI Chapters worldwide to email an introduction/explanation of the survey to their membership and request them to complete the survey by accessing a URL link to Survey Monkey. The respondents were asked to choose the most recent virtual project team that they worked on when answering the questions on the survey. The survey contained a total of 44 questions – 12 covering demographic topics and 32 addressing the eight characteristics outlined above. A total of 521 people responded to the survey.
Table 1 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. The respondents were asked to class their organization as multinational, country indigenous, or consultancy. Table 2 shows that multinational organizations have the highest representation at 67.4%. The spread of the respondents according to industry focus of the organization with which they worked is shown in Table 3. The predominant industry focuses are: information technology (26.1%), other (12.3%), and telecommunications (11.1%). Initial studies of comments in the other selection category show that not-for-profit organizations, retail, and transportation are the most predominant comments.
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 between six months and two years (Table 4). Table 5 shows that 59.9% of the organizations in which the respondents worked employed 20,000 or less. The respondents were asked to enter (in a comment box) their job role on the virtual team they selected. Given that the survey was distributed to past and present members of PMI, it was not surprising that the majority gave their job role as project manager. Over half (53.1%) of the respondents had between one to ten years experience in their job role, and, interestingly, nearly half of the respondents (49.7%) had been working for over twenty years (Table 6).
The survey also requested respondents to rate the performance of their selected projects. Pinto and Slevin's' (1987) four project success factors were used and the results are shown in Table 7. It shows that projects conducted by virtual teams were successful.
As stated, 12 questions on the survey focused on demographic aspects; the key findings of which are outlined above. The remainder of the survey questions (32) were centered on the eight characteristics of virtual teams – temporal, geographic, cultural, social, political, team membership, communication technology, and task complexity. The data findings from these questions are presented next.
The survey asked a number of questions on each of the eight attributes. Many of the questions focused on the physical aspect of team typology – number of members, locations, nationalities, languages, organizations, technology usage, etc. The other questions investigated the impacts of the physical dispersion – temporal, cultural, social, and political. The data results are described for each of the eight characteristics.
The survey investigated the physical temporal dispersion of virtual teams. When asked if all team locations and team members exist within the same time zone, the response was yes = 21.2% (108) and no = 78.8% (402). This indicates that approximately 80% of the virtual teams in the survey experienced time zone dispersion. Table 8 details the physical extent of the dispersion and shows that 34.9% of virtual teams are fully global. In Table 9, we get a picture of the median size of the largest time difference (8 hrs.). Also listed is the median number of nonbusiness hours (4 hrs.) that a team member usually works as a result of temporal dispersion. Due to the high number of outliers that existed in the responses, the median results from the data are used, as they provide more accurate answers.
Using a five-point Likert scale that ranges from 1 (strongly disagrees) to 5 (strongly agrees), participants were asked a number of questions to assess the impact of temporal dispersion. Table 10 lists the findings. It is clear that time zone differences impact both performing tasks in parallel and communication. However, there is not a lack of understanding among team members of the various physiological and social norms/habits of the team members. In addition, time zone differences do not cause missed task deadlines or missed meetings.
The survey data shows that the median size of a virtual team is 15 people and the median number of locations is four. Once again, due to the presence of outliers, median represents a more accurate figure (Table 11). The most popular spread of members across locations is a number of locations with unequal numbers of team members at each location (Table 12). Also, 64.5% (336) of virtual teams had a key/primary/main location.
For the teams surveyed, data collected showed that 13.1% (66) of the teams all had team members of the same nationality and 86.9% (437) of the teams were made up of a number of nationalities. The median figure for the number of nationalities on a team is four. The median number of languages used on a virtual team is one. The survey showed that 92.3% (481) of teams responded that there was one mandatory language used by the team. The breakdown of official/mandatory languages is as follows: English (442), Spanish (12), Portuguese (8), French (4), German (2), Italian (1), Croatian (1), Arabic (1), Polish (1), Romanian (1), Urdu (1). This demonstrates that English is the most common language used by virtual teams.
When asked if all team members were from the same organization, the response was 40.4% (201) yes and 59.6% (297) no. For those teams that consisted of a number of different organizations, the median equals three. The survey finding also showed that for the number of functional areas/departments represented on a virtual team, the median is four. For the number of different subject matter expertise areas represented on a team, the median is five (Table 13).
Table 13 provides information of the physical aspects of culture. Table 14 shows the findings from questions aimed at studying the awareness of various cultures within virtual teams and the impact of cultural diversity on a virtual team. The rating was a five-point Likert scale that ranges from 1 (strongly disagrees) to 5 (strongly agrees). The findings show that team members are good at recognizing different cultural situations, and understand the different economic, legal, and social conditions that exist within a virtual team. Team members also work hard to adapt to different cultures and their communication reflects their sensitivity to different cultures within their team. Regarding organizational culture, the survey findings indicate that despite different organizations working within the team, the dominant culture of one organization persisted and the team used one set of methodologies, processes, and policies. Similarly, for functional culture, the different functional/departmental areas and subject matter expertise areas, used the same set of methodologies, processes, and policies as the virtual team.
For the social attribute (Table 15), the findings show that virtual teams have a vision, as well as goals and objectives, and are aligned to them. All these questions have a rating average of greater than 3.5. Team members are encouraged to and are willing to share their knowledge and information. A team member's expertise is considered more important than title/position. Also, the most popular leader type is one sole leader (39.1%), followed by a number of leaders at different locations (37%) (Table16).
The survey findings indicate that virtual teams are strong politically, with the teams having strong reputations within their organizations, autonomy to run the program as they wish, and containing proven leaders that have a high degree of interaction internally within the team, and externally within the organization (Table 17).
The survey asked respondents to indicate the percentage of fully-dedicated team members, dedicated roles, direct reports, and number of contractors on their team. Table 18 lists the findings. The average rating of 2.23 indicates that ranges of 31–50% of team members are contractors. However, a range of 71–90% (rating = 4.61) of team members have dedicated roles on the team. Another 51–70% (rating = 3.31) reported directly to the project manager/team leader and were also 100% dedicated (rating = 3.43) to the team. Questions (using a five-point Likert scale) were asked to investigate team members' experience of virtual working, familiarity with other team members, diversity of knowledge, and experience of communication technology. Table 19 shows that almost half of the respondents (45.5%) agreed that team members had previous experience of working on virtual teams. Over 42.8% of the respondents indicated that team members had previously worked together. The findings on diversity of knowledge of team members showed that it was high, with an average rating of 4.09. Respondents also agreed that team members were experienced in the use of computer technology (average rating of 4.23).
The data collected found interesting facts on the types and frequency of technology used (Table 20). As stated above, the survey adapts Webster and Wong's (2008) frequency of usage seven- point Likert scale to the following six-point Likert scale – 'Never' (1), 'A number of times in a 6 month period' (2), 'A number of times a month' (3), 'A number of times a week' (4), 'A number of times a day' (5), and 'Almost continuously' (6). The most frequently used technologies are email, phones (fixed and mobile), and instant messaging. Each method has a rating average of greater than 4.0. The next most frequently used tools are data sharing repositories, web portals, and web conferencing with rating averages between 3.0 and 4.0. The least-used tools are standalone video conferencing tools, letter/fax mail, and social networks.
To measure task complexity, the survey used Grattan and Erikson's (2007) task complexity test. While they declare that two or greater true answers to the six statements indicate that a task is complex, this survey further rates the complexity on the number of true answers to all the statements. The findings indicate that virtual teams are used to execute complex tasks, with over 52.6% (255) of the respondents executing tasks with a greater than 3.00 complexity rating (Table 21).
This section has detailed the data results for the eight characteristics of a virtual team typology. These findings are discussed next.
Discussion of Findings
The findings from this survey show a number of interesting aspects on the typology of virtual teams.
Virtual Team Temporal and Geographic Dispersion
The median size of a team is 15 members in four locations, with the greatest time zone difference of eight hours. Virtual teams are mostly global with locations across continents. While the median for nationalities on a team is four, English is the most commonly used language, and in many cases, is mandatory. A review of the literature could not find a similar large scale empirical survey that can corroborate this finding. However, it does support the literature of virtual team size and mix (Henry & Hartzler, 1997; Bal & Teo, 2000; Martin et al., 2004; Dube et al., 2006).
Many researchers (Sarker & Sahay, 2002; Bell & Kozlowski, 2002; Fiol & O'Connor, 2005) point to the communication and cultural barriers resulting from temporal dispersion. However, this research indicates that while time zone differences make doing tasks in parallel difficult and may cause delays in communication; in general, the functional relationships between team members is not impacted. Team members understand each other's social norms/habits and these differences do not cause conflict. Also, time zone difference does not impact meeting attendance or achieving task deadlines. The temporal finding from this research and the positive performance findings support Ahuja's (2010) hypothesis that team distribution does not impact performance.
Virtual Team Culture
Team members on virtual teams have an awareness of the different national cultures within their teams and work to understand these cultures better. They are good at recognizing situations that may arise due to the differing cultures and their communications within their teams reflect their sensitivity to the many cultures. The average (median) number of different organizations working on a virtual team is three. However, the virtual team uses one common set of policies, methodologies, and processes within the team. It is also common that the organizational culture of one of the represented organizations dominates the organizational culture of the team. The median for the number of different functional/department areas on a team is four and the median for the number of different subject matter expertise (SME) areas represented on a team is five. The various departments and SMEs all use the same policies, methodologies, and procedures as those of the virtual team.
Regarding the social attributes of virtual teams, the findings show that one sole leader is the most popular leadership form within a team. Teams are also aligned to a common vision and goals and objectives. The survey also supports research literature, in finding that within virtual teams, expertise and knowledge is considered more important than position/role, and that knowledge dissemination is encouraged and willingly performed. (Bal & Teo 2000; Lee-Kelley, 2000).
Virtual teams tend to have strong reputational capital. The team leaders are proven leaders and interact with their team members and the organizations represented within the team. Also, virtual teams usually have freedom and autonomy in the execution of their projects.
While 23% of the respondents indicated that less than 10% their team were fully dedicated to the team, the average mean is 3.43, which indicates that approximately 60% of team members are 100% dedicated to the project. The mean answer for the number of team members with dedicated roles is 4.61, which represents over 60% of the team. Another 43.4% of respondents indicated that between 91–100% of team members had dedicated roles. Approximately 60% (mean 3.31) also stated that their team members reported directly to the project manager/team leader, and that approximately 40% (mean 2.23) of the team members were contractors.
This research supports the literature that virtual teams are formed to execute complex tasks/projects. Adapting Grattan and Erikson's (2007) complexity test, this research shows that the tasks which virtual teams perform are very complex with over 52.6% of the respondents scoring their team's task complexity at four or greater.
The most frequently used communication technologies amongst virtual teams are email, fixed and mobile phone, instant messaging, and data sharing repositories. The least frequently used tools are social networks, letters, and stand-alone video conferencing. Surprisingly, web conferencing tools are not as frequently used as these authors expected, given the proliferation of these tools in the last number of years. In comparison to a study done by Olson and Olson (2000, p66), this study shows that telephone and email still remain the most frequent communication methods. However, web conferencing is more frequently used now than in 2000.
In summary, the empirical findings provide a picture of the typical typology of a virtual project team. It is a global team of around 15 members across approximately four locations. The project executed by the team is complex, of duration between six months to two years, and costing less than US$5 million. The mix between permanent organization resources and contractors is 60%:40%. Approximately 60% of the team are fully dedicated to the project and report directly to the team leader. The team members have a diversity of knowledge and skills. The primary communication tools used are email and phones. The number of organizations involved in a virtual team is normally three. However, the team only uses one set of organization methodologies, processes, and policies. There is usually one sole leader of the team with a proven track record. The team has strong reputational capital and is aligned to a common vision and goals. Within the team, there is a good awareness of the cultural differences within the team, and while temporal dispersion does cause task execution and communication challenges, overall performance is not impacted.
This paper focuses on the initial findings from a large-scale study of virtual project teams. It outlines the descriptive statistical findings from the study of the eight core attributes of virtual teams – temporal, geographic, social, political, cultural, team membership, task complexity, and communication technology. The next step in the study will be to analyze the findings. Common factor analysis will be conducted in order to see if the measurement items used for many of the attributes can be simplified/grouped and if score factors can be established. Following that, correlation and regression analysis will be conducted to see if any predictions can be established. The robustness of the predictions, if established, will be tested to see if they hold true for the various demographics types or groupings within the survey data.
While the sample size for this survey was large (521), the majority of the respondents were project managers. Therefore, further research is required involving other roles within virtual project teams in order to test the robustness of these findings.
As stated, the objective of this paper was to provide empirical evidence on the typology of virtual project teams that will enable further research into the understanding of the mechanisms and challenges of working in virtual project teams. The data collected from this large-scale survey of virtual teams provides future researchers on virtual teams with empirical data on the typology of virtual teams, which will assist them in defining their research.
Ahuja, J., (2010). A study of virtuality impact on team performance. The IUP Journal of Management Research, 28(5).
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.
Bennett, M. J. (1993). Towards ethnorelativism: A development model of intercultural sensitivity In R. M. Paige (Ed.), Education for intercultural experience (pp. 21–71) (2nd ed.). Yarmouth, ME: Intercultural Press.
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.
Bjorn, P., Ngwenyama, O., (2009), Virtual team collaboration: Building shared meaning, resolving breakdowns and creating translucence, Information Systems Journal, 19, 227–253.
Chudoba, K. M., Lu, M., Watson-Manheim, M. B., & Wynn, E. (2003, December). How Virtual Are We? Measuring Virtuality and Understanding its Impacts in a Global Organisation. Proceedings of the International Conference on Information Systems.
Connaughton, S. L., & Shuffler, M. (2007). Multinational and multicultural distributed teams: A review and future agenda. Small Group Research, 38, 387.
Davidow, W. H., & Malone, M. S. (1992). The virtual corporation. New York: Harper Business.
Domschke, M., Bog, A., Uflacker, M., Zeier, A. (2009). Managing globally distributed engineering teams: A case study on virtual industrial engineering. HP Labs.
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.
Espinosa, J. A., DeLone, W., Gwanhoo, L. (2006). Global boundaries, task processes and IS project success: A field study. Information Technology & People, 19(4), 345–370.
Espinosa, J.A., Pickering, C. (2006). The Effect of Time Separation on Coordination Processes and Outcomes: A Case Study. Proceedings of the 39th Hawaii International Conference on System Sciences.
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.
Geber, B. (1995). Virtual teams. Training, 32, 36–40.
Ghemawat, P. (2001). Distance still matters: The hard reality of global expansion. Harvard Business Review, 79(8), 137–147.
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.
Grattan, L, Erickson, T.J. (2007). Ways to build collaborative teams. Harvard Business Review, 85(3), 104–112.
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.
Hackman, J. R. (1989). Groups that work (and those that don't). San Francisco, CA: Jossey- Bass.
Harvey, M.G., Griffith, D.A., (2007). The role of globalization, time acceleration, and virtual global team in fostering successful global product launches. The Journal of Product Innovation Management, 24, 486–501.
Harvey, M.G., Novicevic, M.N., Garrison, G., (2004) Challenges to staffing global virtual teams, Human Resource Management Review, 14, 275–294.
Henry, J. E., & Hartzler, M. (1997). Virtual teams: Today's reality, today's challenge. Quality Progress, 30, 108–109.
Hofstede G. (1980). Culture's consequence: International differences in work-related values, Beverly Hills, CA: Sage Publications.
Hofstede G. (1991). Cultures and organizations: Software of the mind. London: McGraw Hill.
Johnson, P., Heimann, V., & O'Neill, K. (2001). The "wonderland" of virtual teams. Journal of Workplace Learning, 13, 24–30.
Kim, K., Kirkman, B., Chen, G., (2006). Cultural Intelligence and International Assignment Effectiveness. Academy of Management Best Conference Paper, 2006.
Kimball, L. (1997). Managing virtual teams. Team Strategies Conference sponsored by Federated Press, Toronto, Canada, 1997.
Kirkman, B. L., Rosen, B., Gibson, C. B., Tesluk, P. E., & Mcpherson, S. O. (2002). Five challenges to virtual team success: Lessons from Sabre Inc. Academy of Management Executive, 16, 67–79.
Lee-Kelley, L. (2002). Situational leadership: Managing the virtual project team. Journal of Management Development, 21(6), 461–476.
Lipnack, J., & Stamps, J. (2000). Virtual teams: People working across boundaries with technology (2nd ed.). Hoboken, NJ: John Wiley & Sons.
Ludden, P., Ledwith, A., Lee-Kelley, L., (2012). A Typology Framework for Virtual Teams. Proceedings of the PMI 2012 research congress, Limerick, Ireland, 2012.
Martins E.C., Terblanche, F. (2003). Building organisational culture that stimulates creativity and innovation. European Journal of Innovation Management, 6(1), 64–74.
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.
MacDuffie, J.P., (2007). HRM and distributed work: Managing people across distances. The Academy of Management Annals, 1(1), 549–615.
Nader, A. E, Shamsuddin, A., & Zahari, T. (2009). Virtual teams: A literature review. Australian Journal of Basic and Applied Sciences, 3(3), 2653–2669.
Olson, G.M., Olson, J,S. (2000). Distance matters. International Journal of Human-Computer Interaction, 15, 139–178.
O'Leary, M.B., Cummings, J. (2002). The Spatial, temporal and configurational characteristics of geographic dispersion in work teams. MIT Sloan School of Management. Retrieved from http://ebusiness.mit.edu
Orlikowski, W. J. (2002). Knowing in practice: Enacting a collective capability in distributed organizing. Organization Science, 13(3), 249–273.
Poehler, L., Schumacher, T., (2007, August). The Virtual Team Challenge: Is it Time for Training? PICMET 2007 Proceedings, Portland, OR.
Pinto, J.K., Slevin, D.P., (1987). Critical success factors in successful project management. IEEE Transactions on Engineering Management, 34(1), 22–27.
Powell, A., Piccoli, G., & Ives, B. (2006). Virtual teams: A review of current literature and directions for future research. The Database for Advances in Information Systems, 35(1), 6–36.
Sarker, S., Grewal, R., Sarker, S. (2002). Emergence of Leaders in Virtual teams: What Matters? Proceedings of the 35th Hawaii International Conference on System Sciences.
Sarker, S., Sahay, S., (2003) Understanding virtual team development: An interpretive study, Journal of the Association for Information Systems, 4, 1–38.
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.
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.
Staples, D. S., & Cameron, A. F. (2005). 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.
Thissen, M.R., M.P. Jean, C.B. Madhavi and L.A. Toyia. (2007). Communication Tools for Distributed Software Development Teams. Proceedings of the 2007 ACM SIGMIS CPR Conference on Computer Personnel Research: The global information technology workforce. St. Louis, MI, ACM.
Townsend, A. M., DeMarie, S. M., & Hendrickson, A. R. (1998). Virtual teams: Technology and the workplace of the future. The Academy of Management Executive, 12(3), 17–19.
Trompenaars, F., & Hampden-Turner, C., Riding the waves of culture (2nd ed.). New York: McGraw-Hill.
Watson-Manheim, M.B., Belanger, F. (2002). Exploring communication-based work processes in virtual work environments. Proceedings of the 35th Hawaii International Conference on System Sciences
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.
Zhang, S., Tremaine, M., Fjermstad, J., Milewski, A., & O'Sullivan, P. (2006). Delegation in virtual teams: The moderating effects of team maturity and team distance, IEEE International Conference on Global Software Engineering (ICGSE'06).
Padhraic Ludden is a program manager with Hewlett-Packard. He is also in the third year of a doctoral research program with the Engineering Research Centre, University of Limerick. Mr. Ludden graduated from University College in Galway, Ireland in 1984 with a B Eng (honors) in Industrial Engineering. He has 27 years' experience in the manufacturing sector, with over 20 of those years 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 masters 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 has presented a paper on the Project Management Institute's (PMI®) – OPM3® versus SEI-CMMI at the PMI Global Congress EMEA 2004. 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 Conference 2012. Mr. Ludden has his Project Management Professional (PMP®) certification and is a former president of the PMI Ireland Chapter. He completed the PMI Leadership master class in 2008 and was the PMI EMEA component mentor from 2008–2011. He also served as a member of the PMI Chapter Members' Advisory Group (CMAG) from 2011–2013.
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