A typology framework for virtual teams
In the modern work environment the need for organisations 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 teamwork occurs across many time zones, locations, and organisations. This type of teamwork has lead 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 paper is to develop a typology framework for virtual teams that will assist future researchers in classifying the phenomena of virtual teams into distinct types.
A review of published papers on the nature of virtual teams suggests that there are nine key areas of focus in the characteristics of virtual teams—temporal, geographic, social, culture, historical, technology, political, team membership, and task. This paper adds a tenth characteristic—company type. From the 10 characteristics a standard set of measureable attributes are developed.
The research of frameworks for virtual teams can be classified under three main groupings—typology, input-process-output, and people-technology-process. This paper reviews the frameworks developed by researchers to date and highlights weaknesses in each framework's ability to explore virtual team typology. Using the characteristics and attributes defined, a new framework for exploring the typology of virtual teams is proposed.
Keywords: virtual team, team typology, team characteristics, team framework
In the modern work environment the need for organisations 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 teamwork 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) linked the start of the virtual team, to the early 1990s when the U.S. multinationals and their affiliates overseas began using the team concept in order to integrate their work practices. Increased globalisation and the rapid improvements in communication technology has resulted in a huge growth in the use of virtual teams, with Martin, Gilson and Maynard (2004) contending that nearly all organisational teams are virtual to some extent and Johnson, Heimann and O'Neill (2001) stated 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) showed evidence of a considerable volume of research. Martin et al. (2004) noted 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) stated 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.
The dictionary definition of typology is a systematic classification or study of types. The role of typology in scientific development is to help organise and make sense of complex phenomena. Bell and Kozlowski (2002) stated that by creating a schema that establishes similarities and differences, the scientist endeavours to classify the phenomena into distinct types. The aim of this paper is to explore research into virtual teams in order to develop a typology framework that will assist future research to classify the phenomena of virtual teams into distinct types.
Past publications will be examined in an attempt to develop the predominant thinking on virtual team typology. The objectives of this research are to define a standard set of attributes from the characteristics of virtual teams and to develop a framework using these attributes, which will assist in the exploration of virtual team typologies. First, the research on the characteristics associated with virtual teams is reviewed and the question of defining a standardised set of attributes is explored. Next the various frameworks used in literature are examined. In conclusion, a relationship framework for the attributes that will develop the study of virtual team typology is proposed.
A Review of the Characteristics of Virtual Teams
A review of published papers on the nature of virtual teams suggests that there are nine key areas of focus in the characteristics of virtual teams. This section will outline and discuss these nine areas, as well as the ongoing debate between the use of boundaries or discontinuities to study virtual teams and the key role of technology. Finally, a further characteristic that has received little discussion in the published research is recommended.
It is evident that temporal and geographic distribution is the key characteristic 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 (2003) looked at the impact of task complexity on the time boundary and proposes that the greater the complexity, the greater the need of 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 cultural 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, DeMarie, & 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 impact on the team of the absence of proximal face-to-face interaction (Griffith & Neale, 2001).
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 organisation. The boundaries are those that the study participants repeatedly referred to that shaped and challenged 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 objective (Bal & Teo, 2000; Geber, 1995; Henry & Hartzler, 1997; Lipnack & Stamps, 2000; Nader et al., 2009; Schlenkrich & Upfold, 2009). Lipnack and Stamps (2000) identified the importance of shared leadership, as did Dube, Bourhis, and Jacob (2006) in their proposed 18 structured characteristics of virtual communities of practices. A structuring characteristic is defined as the “rather” stable elements of a virtual community of practice (VCOP). These are similar to the “rather stable” elements of a person—age, height, race, etc. Dube et al. (2006) argued that most of the characteristics are a result of design decisions when the VCOP begins and that while some will positively influence the VCOPS life, others will create challenges that will require actions. Another characteristic is that virtual teams exist primarily in flat structures that have integrated levels and are cross organisational (Lipnack & Stamps, 2000).
The research into the culture of virtual teams can be classified into four categories—national, organisational, 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 et al., 2006; Espinosa, Delone, & Gwanhoo, 2006; Schlenkrich & Upfold, 2009; Watson-Manheim, Chudoba, & Crowston, 2002). However, equal importance is given to the impact of the diverse organisational 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 (Gibson & Cohen, 2003; Espinosa et al., 2006) as traits of virtual teams.
The historical boundary focuses on the life cycle and lifespan of the team, which is often related to the type of task being executed. The age and permanence or impermanence of the team is also a subject of inquiry. From a historical perspective, the literature research studies the life cycle, age, and permanent or temporary nature of virtual teams (Connaughton & Shuffler, 2007; Dube et al., 2006; Schlenkrich & Upfold, 2009). Virtual teams are found to have short life cycles and short life spans, and are mostly temporary entities. Bell and Kozlowski (2002) proposed that task complexity also impacts the permanent/temporary nature of the team, with teams executing more complex task normally having a greater permanency and lifespan. Dube et al. (2006) included lifespan, age, and level of maturity as three of the 18 structural characteristics.
All virtual teams utilise computerised media communication. Bal and Teo (2000) viewed technological communications for the way it enables the team. Lee-Kelley (2002) highlighted the extensive use of technology for communication, information, and coordination purposes in order to overcome the constraint of geographical dispersion. Other researchers emphasis the dependency on technology, with the greater the geographic dispersion the greater the dependency (Gibson & Cohen, 2003; Dube et al., 2006; Zhang, Tremaine, Fjermstad, Milewski, & O'Sullivan, 2006). While technology is not an attribute of Bell and Kozlowski's (2002) 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).
Due to the increased level of boundary crossing interactions (Bal & Teo, 2000; Lipnack & Stamps, 2000), the greater number of interaction and affiliations between organisations, and the multileveled relationships within organisations (Watson-Manheim et al., 2002), that are common in virtual teams, politics plays an important role in the functioning of virtual teams.
Team members are a key focus in the research of virtual teams. The central themes for team membership are member skill set, temporal nature/dynamism of the team, 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, many are contractors, and that many multitask across teams (Chudoba et al., 2003; Lee-Kelley, 2002; Nader et al., 2009; Schlenkrich & Upfold, 2009; Watson-Manheim et al., 2002; Zhang et al., 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).
The nature of the task being conducted by the virtual team is considered important in the research literature. Task design, composition, interdependency, and complexity impacts the makeup and functioning of the team (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. Appendix 1 summarises the research into the nine characteristics and associated attributes of virtual teams.
Boundaries versus Discontinuities
Early research into virtual teams focused on characteristics and boundaries that determined virtuality (Bal & Teo, 2000; Geber, 1995; Lipnack & Stamps, 2000). The terms characteristics and boundaries are interchanged. For example, Bal and Teo (2000) list characteristics as geographically dispersed, driven by common purpose, involved in cross-border collaboration, enabled by communication technology, not a permanent team, inconsistent membership, and teams of knowledge workers. Orlikowski (2002) identified virtual team boundaries as temporal, geographic, social, cultural, historical, which are similar to the characteristics listed by Bal and Teo. The work of Watson-Manheim et al. (2002) introduced the concept of discontinuities in an attempt to provide a framework to classify different virtual work environments. They stated that the common thread that tied together virtual work was the notion of discontinuity. However, the discontinuities that they identify—physical location, temporal location, work group membership, organisational affiliation, relationship with an organisation, and culture are little different from the characteristics or boundaries identified by previous research. Chudoba and Watson-Manheim (2008, p. 57) stated that boundaries are objective (i.e., recognizable by all parties, even those not actually involved in the communication process), and discontinuities are subjective (i.e., relevant only as perceived by those involved in the communication process). For the purpose of this study differentiating between boundaries and discontinuities is not warranted, as both a boundary and a discontinuity contribute in equal measure to virtuality in a work environment. Also, does the objective versus subjective argument hold true? For example, while physical distance can be interpreted as a boundary, is it not how the resources perceive the increased effort resulting from distance as the measure of virtuality. Research also shows that regardless of the choice of boundaries or discontinuities the identified lists are very similar (Table 1). Thus, this research will not differentiate between boundaries and discontinuities. Instead, the focus will be to identify characteristics and by research determine the perceived impact on virtuality of these characteristics.
For the characteristic of technology, the common underlying theme in research to date is that a virtual team is dependent on technology to communicate. Early research was valid in its argument that the key difference between virtual teams and traditional teams was that virtual teams were dependent on technology to communication. However, in this modern age, this argument is no longer valid, as traditional/co-located teams also have a dependency on technology to function and communicate. Therefore the focus when investigating the boundary of technology should not be on dependency, but more on the quality and richness of the communication technology available to the team, and the extent that team members utilise technology to counteract the lack of face-to-face communication.
|Social||Work group membership|
|Historical||Relationship with an organisation|
In the review of the literature little attention is given to the type of organisation to which the researched team belongs. While many researchers focus on the size of the team, they do not investigate the impact of the organisational structure within which the team resides. In particular, there is no study of the different influence that multinationals, national, and local organisations have on virtual teams working within their structures. For example, a well-established multinational may have a very strong company culture that permeates and mitigates national culture boundaries, organizational-wide processes that mitigate team interaction boundaries and established global technology networks and tools that mitigate dispersion boundaries. Thus, this research proposes that a virtual team typology must have as a characteristic the company/parent type within which the virtual team exists.
A Standardised Set of Attributes
The first question posed by this research is: Can the attributes associated with the characteristics of virtual teams be standardised? The review of the literature shows that there is considerable similarity and overlap of the attributes of the characteristics chosen by researchers to define and study virtual teams. Appendix 1 illustrates this fact. All publications identify time zones as the attribute of the temporal characteristic. For geography, the elements of study can be summarised as location and physical distance. The areas of focus for the social characteristic are goals, common purpose, and leadership. There is a broad area of study for the characteristics of culture varying from thrusting relationships to gender diversity. However, these studies can be grouped into three categories—functional, organizational, and national. Permanence, life cycle, and maturity are the main subjects explored when researching the historic context of virtual teams. This research proposes that the attributes of age, lifespan, and life cycle adequately cover the historical characteristic. The impact of technology on virtual teams is studied from the point of view of dependency, utilisation, and the richness of the computerised environment. Due to the dispersion of a virtual team across many resources, locations, and organisations, the political characteristic of a virtual team is centred on collaboration and affiliation. The study of the membership of a virtual team has produced the largest volume of research, which can be summarised under the attributes of skill, experience, role, size, and interaction. For the task characteristic the focus is on size, composition, interdependency, and type, which can be summarised under the attribute complexity. As stated in the previous section on company type, the attribute that requires study is type (for example, multinational, indigenous, consultancy, etc.). Table 2 shows the refinement of the table in Appendix 1 into 10 characteristics (with the addition of company type) with 23 measureable attributes.
A standard set of measurable characteristic attributes with which to study virtual teams is proposed in Table 2. This set is developed from a review of publications on the nature of virtual teams. However, Table 2 does not explore the relationship between the listed characteristics. The next section will explore if these characteristics and attributes can be developed into a framework for defining the typology of a virtual team.
|1. Temporal||1a. Time zone|
|2. Geographic||2a. Location |
|3. Social||3a. Common purpose |
|4. Cultural||4a. Functional |
|5. Historical||5a. Age |
5c. Life cycle
|6. Technology||6a. Utilisation |
|7. Political||7a. Collaboration |
|8. Team membership||8a. Skill |
|9. Task||9a. Complexity|
|10. Company||10a. Type|
Review of Virtual Team Frameworks
The research of frameworks for virtual teams can be classified under three main groupings—typology, input-process-output, and people-technology-process. This section will first review the frameworks developed by researchers to date and then highlight weaknesses in the frameworks if they are required to explore virtual team typology. A new framework is then proposed.
Some of the typology frameworks are proscriptive in nature. Based on a number of dimensions, a virtual team is given a defined classification (Evaristo & Van Fenema, 1998; Fisher & Fisher, 2001; Kirkman & Mathieu, 2005; Lipnack & Stamps, 2000). The models of Bell and Kozlowski (2002), Griffith, Sawyer, and Neale (2003), Fiol and O'Connor (2005) define virtuality along a continuum, moving from traditional/collocated, to hybrid, to pure virtual. Bell and Kozlowski introduced task complexity as the overriding factor of where a team will lie on the continuum, while Fiol and O'Connor use their framework to test a number of hypothesis based on predominant antecedents (uncertainty reduction, self-enhancements ) and moderating effects (individual, communication context, team and situational). The structuring characteristics model proposed by Dube et al. (2006) is also proscriptive in that it measures virtuality against 18 characteristics. A number of studies build exploration frameworks around a single aspect of a virtual team. Griffith and Sawyer (2006) used the basis of their three-dimension typology to build a knowledge management system framework to study knowledge transfer in virtual teams, while Gerda, Kandela and Kulno (2009) developed a framework based on communication specifics. Apart from Dube et al., which verified the proposed model against three virtual communities of practice, and Gerda et al. that verified their model in a large-scale survey of the Estonian service industry, the other typology models are conceptual and have not being verified by practical application. Table 3 lists the typology models.
These frameworks use the Input-Process-Output (I-P-O) model originally developed to study group effectiveness (McGrath, 1984; Hackman, 1989), and it is maybe for this reason that the primary aim of many of the frameworks is to measure how various variables (characteristics, boundaries, discontinuities) impact the effectiveness of the team (Andriessen & Verburg, 2004; Espinosa et al., 2006; Kirkman & Mathieu, 2005; Staples & Cameron, 2005). Martin et al. (2004) and Powell et al. (2006) used their I-P-O frameworks to classify their findings from a review of virtual team literature. Gibson and Cohen's (2003) design factors, enabling conditions and outcomes model is controlled by the two key moderators of degrees of virtuality and difference. They defined moderators as factors that amplify the effects of design factors on the enabling conditions.
A central aim of this research paper is to develop a typology framework to enhance the study of virtual teams. While the I-P-O frameworks reviewed do identify many of the common characteristics that contribute to our understanding of virtual teams, they do not utilise these characteristics to better define team typologies. Instead, these characteristics are used solely as input variables into the study of team effectiveness. This suggests that the I-P-O frameworks are insufficient models for developing the knowledge of virtual team typology. The I-P-O frameworks are shown in Table 4.
|Model Type||Model Name||Dimensions||Purpose|
|Typology||Space, Time, Org.—Lipnack & Stamps (2000)||Space, time, organisational boundaries||Position teams on a space, time, organisational matrix|
|Space, time, and culture—Fisher & Fisher (2001)||Three-dimensional model with axis of space, time and culture Teams classified into six types based on a combination of same or different space, time or culture measurements (e.g., same space, different time, same culture)||Classify a team against six different types|
|Types of teams—Duarte & Snyder (2006)||Seven team classifications—networked, parallel, project/product/development, work production, service, management, action||Classify a team against the seven classifications|
|Types of teams /degrees of Virtuality—Schlenkrich & Upfold (2009)||Enhancement of Duarte and Snyder model. Classifications rated against degree of virtuality||Classify a team against the seven classifications and indicate how virtual it is|
|Team structure—Evaristo & Van Fenema (1998)||Location (single, multiple) Project (single, multiple)||Classify a team based on location and project|
|Two dimensions of virtualness—Griffith & Neale (2001)||-Level of communication and document support |
-Time spent working apart
|Measure where a team is on the virtual continuum between traditions – hybrid – pure|
|Three dimensions of virtualness—Griffith & Neale (2003)||-Level of technological support(low-high) |
- Physical distance (Close–far)
- % time apart on task (0-100)
|Teams are categorised based on the three dimensions|
|Three dimensional model of team virtuality—Kirkman & Mathieu (2005)||-Extent of use of virtual tools (low-high) |
-Informational value (low-high)
|Measure virtuality based on three dimensions|
|Three dimension knowledge mgmt. Framework—Griffith &Sawyer (2006)||-Knowledge entry into the system (active to passive) |
-Kind of content included in the system (person type, knowledge type, information type)
-How users accrue the knowledge (proactive – embedded)
|Study the transfer of knowledge in a virtual environment|
|Virtual team typology—Bell & Kowzloski (2002)||-Member roles |
- Temporal distribution
|A typology for teams based on the four dimensions, along a continuum based on task complexity|
|Virtual—F2F-Hybrid model—Foil & O'Connor (2005)||-Uncertainty reduction |
- Self enhancement
|A complex model describing pure virtual, hybrid and face-to-face teams|
|VCOP Typology—Dube et al. (2006)||18 structural characteristics||Teams are measured against each of the characteristics to determine virtuality|
|Communication specific framework for virtuality—Gerda et al. (2009)||-Richness of communication |
-Time spent communicating
-Frequency of communication
|Study level of virtuality from the viewpoint of communication|
|Model Type||Model Name||Dimensions||Purpose|
|Input, Process, Output (I-P-O)||Design factors, enabling conditions and outcomes model—Gibson & Cohen (2003)||Moderators—degrees of virtuality and differences |
-Design factors (context, group structure, technology, people and process)
-Enabling conditions (Shared understanding, integration and thrust)
-Outcomes (Business and human)
|Explore how moderators impact the design factors and enabling conditions to produce business and human outcomes|
|Virtual team framework Andriessen and Verburg (2004)||-Individual goal directed behaviour and cognitive processes |
- Interpersonal and group processes
- Macro social perspective
|Using inputs of tools, persons, task, structure, and culture and space time. With communication has the key process, examines the impact on the outputs—individual rewards, group vitality and organisational outcomes.|
|IPO model for virtual team functioning—Martin et al. (2004)||-Team inputs |
- Team outcomes
- Moderators of virtual team performance
|Framework was used to classify and organise the literature on virtual teams|
|Global boundaries IPO Framework—Espinosa et al. (2006)||-Global boundary variables (Inputs) |
- Coping task processes
- Project success variable (outputs)
|Model used to examine how global team boundaries, and Coping process variables impacted IS project success|
|Work team effectiveness model—Kirkman & Mathieu (2005)||-Inputs – Contextual features, task – media affordance, temporal issues |
-Process – Team virtuality
-Output – Team effectiveness
|Used to examine virtuality|
|IPO classification—Powell et al. (2006)||Inputs – Design, culture, technical, training |
processes- socio emotional, task
Outputs – Performance, satisfaction
|Used the framework to classify their findings from review of the literature on virtual teams|
|Effectiveness Framework—Staples & Cameron (2005)||-Inputs – Group task design, group characteristics, organisational context, supervisory behaviour |
-Outputs – Effectiveness
|Used to study team effectiveness|
The other framework group identified by this research is the people-technology-process group. The general format for these frameworks is a listing of team characteristics used to study virtual teams grouped under the categories of people, technology, and processes. The frameworks of Lipnack and Stamps (2000) and Bal and Gundry (1999) described the people traits, and technology and process requirements necessary to achieve a high level of virtual team performance. The framework developed by Chudoba et al. (2003) is actually a list of 18 questions that form the basis of a 12-point index for measuring virtuality. This model was tested and verified in a case study of the Intel Corporation. While the characteristics used in the People-Technology-Process frameworks provide the necessary attributes to study virtual teams, the frameworks do not prioritise or allocate importance to various characteristics—this is an inherent weakness in these models. Table 5 summarizes the literature on virtual team typology frameworks.
|Model Type||Model Name||Dimensions||Purpose|
|People-technology-process||People, purpose and links framework—Lipnack & Stamps (2000)||-People (independent members, shared leadership |
- Purpose (cooperative goals, interdependent tasks
-Links (multiple media, boundary cross interactions)
|A framework for studying virtual teams|
|People, Technology, Process model- Bal and Gundry (1999)||-People – Team selection, reward structure, meeting, Specify objectives |
-Technology – security, selection, location, training
-Process – Alignment, structure, team facilitation, performance measurement
|An adoption of Lipnack and Stamps model for studying virtual teams|
|Virtual Index—Chudoba et al. (2003)||12-point index under the groupings of: |
-variety of practice
|A 12-point index to measure virtuality|
Weaknesses of Current Frameworks
The review of the literature identifies some weaknesses in the frameworks. The space, time, and organisation typology model of Lipnack and Stamps (2000), and the location, project model of Evaristo and Van Fenema (1998) are over simplistic, using too few characteristics to adequately examine the nature and dynamics of a virtual team. Duartes and Synders’ (1999, 2006) types of team model is over proscriptive and the categories are more in line with traditional team types rather than an exploration of virtual teams. While Schlenkrich and Upfold (2006) refined the model by ordering the categories in degrees of virtuality, this still leaves us with a model that does not address the complexities of the modern virtual team. Griffith, Sawyer, and Neale's (2003) dimensions of virtuality model and the Kirkman and Mattieu (2005) antecedents’ model do provide good tools for measuring the virtuality of a team, but they still ignore cultural, social, and membership characteristics that must be considered in order to provide a systemic understanding of the nature of a virtual team. Similarly, the single characteristic models of Griffith and Sawyer (2006) and Gerda et al. (2009) provided strong exploration frameworks, but they also were limited in their focus. The work of Bell and Kowzloski (2002) gave a more adequate framework for positioning a team on the virtual continuum in that it incorporates member role, lifecycle, boundaries, and temporal distribution in its measurements. However, their model is purely conceptual and remains unverified by empirical and practical research. The Dube et al. (2006) VCOP framework is primarily a list with simple scoring methods, which is too broad for application to virtual teams. The criticism of the I-P-O models is that they present a list of characteristics without any importance or impact weightings allocated and they are focused primarily on measuring team effectiveness, rather than using the input characteristic variables to define virtual team typologies. Many of the I-P-O frameworks were only developed to classify and organise the literature on virtual teams, rather than investigating virtual team typology. The people-technology-process frameworks do provide a more holistic approach to the study of virtual teams and include many of the factors that influence a virtual team-people, technology, process, purpose, and links. The 12-point virtual index of Chudoba et al. (2003) captures the key characteristics for measuring virtuality, but like the I-P-O models it (and the other people-technology-process models) treats all characteristics of equal importance.
The key focus of this study is to explore the typology of virtual teams in an effort to establish common patterns. As the primary functions of the models listed in Tables 3, 4, and 5 are to measure how virtual a team is, or how effectively a virtual team will perform, these frameworks are inadequate for the purpose of this research. The next section proposes a framework suitable for studying the typology of virtual teams.
The Virtual Team Typology Grid
In order to address the weaknesses highlighted a new model using the standardised attribute criteria defined earlier (as presented in Table 2) is proposed. The model will first be defined, followed by a description of how it will be used.
One of the main concerns for the I-P-O and people-technology-process frameworks was that all characteristics were of equal weighting. However, an examination of these characteristics suggests that task and technology are of greater importance. Technology richness and task complexity have overriding impacts on the level of virtuality of the other characteristics. Technology acts as an enabler of virtuality in that a rich computerised media communication environment can mitigate the negative impacts of a dispersed and diverse virtual team. Task complexity acts as an inhibitor of virtuality as the greater the complexity of the task, the greater the effort required to overcome the dispersion and diversity. Therefore, technology and task complexity are two characteristics of virtual teams that have a greater importance than the other characteristics. In order to reflect this weighting a grid framework is proposed with the technology and task characteristics represented as two distinct columns, and the other eight characteristics presented as equal rows on the grid. This will allow us to study the impact these two characteristics have on the other common virtual characteristics. For example, do teams executing highly complex tasks generally exist in the same time zone and location as suggested by Bell and Kowzloski (2003)? Do teams with multiple time zones and/or multiple locations generally use a rich technology medium? Table 6 shows the proposed typology framework.
|Characteristic||9. Task||6. Technology|
|Attribute||9a. Complexity||6a. Utilisation||6b. Richness|
|1. Temporal||1a. Time zone|
|2. Geographic||2a. Location |
|3. Social||3a. Common purpose |
|4. Cultural||4a. Functional |
|5. Historical||5a. Age |
|7. Political||7a. Collaboration |
|8. Team membership||8a. Skill |
|10. Company||10a. Type|
Table 6 is a high-level view of the framework. At this stage, the metrics criteria for each of the attributes are not yet defined. When defined, these metrics will be included in the grid, an example of which is shown in Figure 1. Please note that the scales in the figure are for explanation only, and that future research will define the metrics for the attributes shown. The typology grid will be used to develop a survey and the findings from the study will then be statistically analysed to see if common patterns or types can be determined for virtual teams.
Based on a review of the literature on the characteristics of virtual teams, this study has defined 10 key characteristics that will help in the understanding of virtual teams. A framework is also proposed that gives weighting to the characteristics and provides a basis for exploring the typology of virtual teams. Although the framework has provided a standard set of attributes for studying virtual teams, research is required to define measurements and scales for each of these attributes. The next stage of this research will be a further literature review in order to establish metrics and scoring mechanisms for each of the attributes on the typology framework.
This research suggests that although there is a considerable amount of research into virtual teams, the level of empirical research is weak. As stated previously, the majority of virtual team frameworks is conceptual and lack verification by practical research. Therefore, following the development of metrics and scoring mechanisms for the attributes on the framework, the next stage of this research will be the verification of the framework by a large-scale practitioner study. The aim of the study will be to explore the ability of the framework to identify common typology patterns for virtual teams.
This paper reviewed the literature on virtual teams and identified a common set of criteria to study the typology of virtual teams. Published frameworks for exploring virtual team types have also been reviewed. The study has examined past and current literature, and based on these findings has identified a standard group of characteristics and attributes. Using these attributes a typology grid for researching virtual teams is proposed. The next step in this research is to develop metrics and scoring mechanisms for each of the attributes. Following this, a comprehensive large-scale survey will verify the model and attempt to determine common typologies for virtual teams.
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|1. Temporal||Temporal distribution (Bell & Kozlowski, 2002; Chudoba et al., 2003; Connaughton & Shuffler, 2007; Espinosa et al., 2006; Nader et al., 2009; Schlenkrich & Upfold, 2009; Watson-Manheim et al., 2002)|
|2. Geographic||Geographically dispersed (Geber, 1995; Henry & Hartzler, 1997; Bal & Teo, 2000; Lee-Kelley, 2002; Bell & Kozlowski, 2002; Watson-Manheim et al., 2002; Chudoba et al., 2003; Cohen & Gibson, 2003; Gibson & Gibbs, 2006; Espinosa et al., 2006; Zhang et al., 2006; Dube et al., 2006; Schlenkrich & Upfold, 2009; Schweitzer & Duxbury, 2010) |
Physically distributed members (Wong & Burton, 2000; Schlenkrich & Upfold 2009)
Assynchronicity (Schweitzer & Duxbury, 2010)
Space and modality, Degree of distribution (Connaughton & Shuffler, 2007)
|3. Social||Common goals and objectives (Geber,1995; Lipnack & Stamps, 2000; Henry & Hartzler, 1997; Bal & Teo, 2000; Nader et al., 2009; Schlenkrich & Upfold, 2009) |
Shared leadership (Lipnack & Stamps, 2000)
Integrated levels (Lipnack & Stamps, 2000)
Co operative goals (Lipnack & Stamps, 2000)
Organisational supervision (Staples & Cameron, 2006)
Creation process (Spontaneous /intentional) (Dube et al., 2006)
Leadership (Dube et al., 2006)
|4. Cultural||Thrusting relationships (Lipnack & Stamps, 2000) |
Relationship with culture (Watson-Manheim et al., 2002)
Culture (Cohen & Gibson, 2003; Dube et al., 2006; Schlenkrich & Upfold, 2009)
Cultural differences (Espinosa et al., 2006)
Number of national cultures (Zhang et al., 2006)
Organisation and function (Cohen & Gibson, 2003)
Organisational context (Staples & Cameron, 2006)
National diversity (Gibson & Gibbs, 2006)
Organisational differences (Espinosa et al., 2006)
Degree of institutionalised formalism (Dube et al., 2006)
Organisational slack (Dube et al., 2006)
Functional diversity (Espinosa et al., 2006; Schlenkrich & Upfold, 2009) Gender diversity (Schlenkrich & Upfold, 2009)
Boundary spanning (Bell & Kozlowski, 2002; Dube et al., 2006; Schlenkrich & Upfold, 2009)
Language (Cohen & Gibson, 2003; Espinosa et al., 2006)
|5. Historical||Lifecycle (Bell & Kozlowski, 2002) |
Lifespan (permanent /temporary) (Dube et al., 2006, Schlenkrich & Upfold, 2009)
Age (Dube et al., 2006; Schlenkrich & Upfold, 2009)
Team permanence/impermanence (Connaughton & Shuffler, 2007; Schlenkrich & Upfold, 2009)
Level of maturity (Dube et al., 2006)
|6. Technology||Computerised media communication (Geber, 1995; Henry & Hartzler, 1997; Bal & Teo, 2000; Bell & Kozlowski, 2002) |
Extensive deployment of technology for information, communication and coordination purposes (Lee-Kelley, 2002)
Technology (Chudoba et al., 2003; Martin et al., 2004; Connaughton & Shuffler, 2007; Schlenkrich & Upfold, 2009)
Electronic dependency (Cohen & Gibson, 2003; Gibson & Gibbs, 2006; Dube et al., 2006)
Communicational distance—reliance on CMC (Zhang et al., 2006)
|7. Political||Boundary crossing interactions (Lipnack & Stamps, 2000; Bal & Teo, 2000) |
Organisational affiliations (Watson-Manheim et al., 2002)
Relationship with an organisation (Watson-Manheim et al., 2002)
Environment (Dube et al., 2006)
Cross boundary collaboration (Nader et al., 2009)
|8. Team membership||Team members are knowledge workers (Bal & Teo, 2000) |
Skilled (Lee-Kelley, 2002)
Contractors/outsourcing partners (Lee-Kelley, 2002)
Decentralised (Lee-Kelley, 2002)
Multi-company workers (Lee-Kelley, 2002; Zhang et al., 2006; Nader et al., 2007)
Multi-tasking (Lee-Kelley, 2002; Schlenkrich & Upfold, 2009)
Member role (Bell & Kozlowski, 2002)
Temporary team (Bal & Teo, 2000; Nader et al., 2009)
Knowledge skills and abilities (Martin et al., 2004)
Team composition (Staples & Cameron, 2006)
Prior global experiences (Espinosa et al., 2006; Dube et al., 2006)
Team belief and process (Staples & Cameron, 2006)
Team members heterogeneity –cultural and organisational (Wong & Burton, 2000; Schlenkrich & Upfold, 2009)
Members selection process, enrollment (Dube et al., 2006)
Members ICT literacy (Dube et al., 2006)
Functional (Educational) diversity (Schlenkrich & Upfold, 2009)
Team does multiple reporting (Schlenkrich & Upfold, 2009)
Interdependent members (Lipnack & Stamps 2000; Henry & Hartzler, 1997; Bal & Teo, 2000)
Inconsistent membership (Bal & Teo, 2000)
Structural dynamism (Gibson & Gibbs, 2006)
Work group membership (Watson-Manheim et al., 2002; Chudoba et al., 2003)
Low team history (Wong & Burton, 2000)
Relationships between members are lateral and weak (Wong & Burton, 2000)
Small team size (Henry & Hartzler, 1997; Bal & Teo,2000; Martin et al., 2004; Dube et al., 2006; Nader et al., 2009)
History of the team (Connaughton & Shuffler, 2007)
|9. Task||Large strategic, operational/commercial (Lee-Kelley, 2002) |
Task complexity (Bell & Kozlowski, 2002; Connaughton & Shuffler, 2007)
Task and composition (Martin et al., 2004)
Team task design (Staples & Cameron, 2005)
Interdependent tasks (Lipnack & Stamps, 2000; Schlenkrich & Upfold, 2009)
Novel task (Wong & Burton, 2000)
Task context/dependency (Espinosa et al., 2006)
Orientation – Operational to strategic (Dube et al., 2006)
Non-routine tasks (Schlenkrich & Upfold, 2009)
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