virtual team management research paper

ORIGINAL RESEARCH article

Virtual teams in times of pandemic: factors that influence performance.

• 1 School of Computing, Tecnológico de Costa Rica, Cartago, Costa Rica
• 2 Department of Financial Economics and Operations Management, University of Seville, Seville, Spain

In the digital age, the global software development sector has been a forerunner in implementing new ways and configurations for remote teamwork using information and communication technologies on a widespread basis. Crises and technological advances have influenced each other to bring about changes in the ways of working. In the 70’s of the last century, in the middle of the so-called oil crisis, the concept of teleworking was defined using remote computer equipment to access office equipment and thus avoid moving around using traditional vehicles. Then from the 90s, with the advent of communications and the widespread use of the Internet, the first virtual work teams were implemented in software development companies that already had some of the important characteristics needed to work in this way, such as, cultural diversity, characterized tasks, geographical distribution of members, communication, interdependence of tasks, leadership, cohesion, empowerment, confidence, virtuality. This manuscript groups the main factors into different models proposed by the literature and also analyzes the results of a study conducted in the midst of the Covid-19 crisis on 317 software development teams that had to work in virtual teams (VT). The results of the quantitative methodology with structural equation modeling based on variance using the partial least squares route method are analyzed. The results of the research focus on some determinants that can directly affect the performance of the virtual team. A first determinant is communication in relation to the tasks. The second is trust in relation to leadership, empowerment and cohesion. The results of virtual teams provide information that can serve as a basis for future research lines for the implementation of virtual work strategies in post-pandemic work.

Introduction

The digital era has meant a change in the processes and routines of the business dynamics to which many organizations have had to adapt in order to compete and survive in globalized markets. The virtualization of organizational life and the digital transformation of labor relations goes hand in hand with the accelerated advance of technologies such as cloud computing, which have made it unnecessary to have tangible servers, software and hardware infrastructures in the company offices and many processes are being carried out by accessing personal equipment or terminals (computers, laptops, and mobile devices) connected to an increasingly fast Internet network. All this is possible thanks to the technology of virtualization ( Sánchez, 2017 ). Recent studies have analyzed the attitude of human resources to cloud technology and its importance in software as a service application - SaaS- ( Palos and Correia, 2017 ) and how the attitude of the worker has changed, thanks to online work training ( Palos-Sanchez, 2017 ). Thus, the digital virtualization of traditionally physical technological resources is also happening at the level of human resources, because increasingly the presence of workers in the same place is not necessary. This implies an immense challenge for the new electronic leadership of teams of collaborators who are increasingly dispersed geographically.

In the beginning, virtual teams were formed to facilitate joint creation and innovation among global or regional experts who did not have enough time to travel to fulfill the specialized tasks of the projects that required them. Today, virtual teamwork has evolved to a point where online collaboration is a way of working for national companies and more naturally for multinational or regional companies. The idea of virtual collaboration between workers, or virtual teamwork VT, consists of a team working together from different physical locations using collaborative ICTs. In the last 20 years this modality has been in constant growth due to the evolution and maturity of the digital era in terms of speed of telecommunications, the power of the computer equipment, the naturalness of adaptation to the use of ICTs in the work of digital natives (born since 1990) and digital migrants (born before 1990). However, at the beginning of the 21st century it was difficult to have faith in VTs due to the low level of maturity of virtual teams which made companies skeptical about the efficiency of this way of working. By the early 2000s, studies showed that the number of VTs that achieved their goals was not very encouraging and there was a significant failure rate. A few years later, things had not changed that much either. In 2004, there was talk of significant challenges in the implementation of virtual teams ( Piccoli et al., 2004 ). Another study ( Brett et al., 2006 ) revealed that most people thought that virtual communication was not as productive as face-to-face interaction, while half of the respondents said they were confused and overwhelmed by collaboration technology. Even so, this happened a few years ago and as technology advanced, companies matured with the use of ICT tools, so these early conclusions from the beginning of the century were not believed to be accurate anymore. A more recent study in 2009, involving 80 global software teams, indicated that well-managed virtual teams using virtual collaboration can outperform face-to-face (FtF) teams.

Additionally, a number of studies ( Jarrahi and Sawyer, 2013 ), indicate that virtual or remotely distributed team collaboration can also improve employee productivity. Therefore, an important question is: what can make a virtual team have better performance results than a face-to-face team? The answer has been provided by several studies that have summarized input factor models and their relationships with other factors grouped into socio-emotional and task-oriented processes and finally their relationships with output factors ( Powell et al., 2004 ; Gilson et al., 2015 ).

In addition to the aforementioned triggers of virtualization of organizational life and the digital transformation of processes ( Zúñiga Ramirez et al., 2016 ) and the interrelations of stakeholders as co-creators of value ( Martinez-Cañas et al., 2016 ; Ribes-Giner et al., 2017 ), it is also worth mentioning that the origin of remote work in a virtual team is originally teleworking.

Considering the above reasons and in view of finding ourselves in the midst of a rapidly evolving digital era coupled with a pandemic that has forced workers in many areas to perform remote work ( Velicia-Martin et al., 2021 ) and aligned with an effective strategy to contain and mitigate rate of spread of infection ( Brooks et al., 2020 ), this study has been undertaken in the midst of the COVID19 impact on virtual teams in the software development industry. The co-creation in virtual teamwork is a very important feature.

The main objective of this research, at a time with a pandemic and the current digital era ( Chen et al., 2020 ), is to analyze the relationship of important factors found in the literature by analyzing the performance of 317 software engineers in virtual teams. Software engineers, due to their training and experience, belong to virtual teams that include co-creation for the construction of software using agile methodologies and have recently been involved in working in virtual teams. This research is original because of the importance given to endogenous variables such as communication and trust. For this reason, the results of the survey carried out have served to understand what role different factors play in the performance of a group used to doing remote or virtual teamwork as part of their normal work. The study uses a structural equation approach with partial least squares (PLS) to evaluate the proposed performance model. The research is organized as follows. First, the Introduction explains the article based on the history of co-creation in current software development and its relationship to the study of vital equipment. Then there is a literature review, which analyzes relevant research on factors in VTs. Thirdly, methodology and justification of the hypotheses are presented. The results are then analyzed. In the Conclusions section, discussions and conclusions are made in which the practical implications of the research are given.

Literature Review

A virtual team is defined as a group of people or stakeholders working together from different locations and possibly different time zones, who are collaborating on a common project and use information and communication technologies (ICTs) intensively to co-create. It can be seen that one of the main characteristics is virtuality, which implies physical and temporal distance between members and a shared purpose ( Ebrahim et al., 2009 ).

Another essential characteristic of virtual teams, which differentiates it from traditional “face-to-face” (FtF) teams is the collaborative use of technology for work. This has been the result of the evolution of ICTs in this digital age, along with the trend toward globalization. In VTs there is naturally a geographical dispersion that entails certain cultural differences and social bonds are more difficult to achieve. All this generates a series of difficulties for communication between members and emotional relationships ( Duarte and Snyder, 2006 ; Lin et al., 2008 ; Shuffler et al., 2010 ).

Virtual teams are affected by a series of factors and phases, which have been investigated in the literature ( Abarca et al., 2020 ) and which give rise to different models for studying and relating them for performance. There are several models of VTs, from classical ones ( Martins et al., 2004 ; Powell et al., 2004 ) to a recent one ( Dulebohn and Hoch, 2017 ). Others analyze VTs at the management level ( Hertel et al., 2005 ) and others analyze them as a systemic Input-Process-Output or IPO ( Saldaña Ramos, 2010 ). This last model is based on others that studied face-to-face teams ( Hoch and Kozlowski, 2014 ) and proposes adaptations to the model when studying VT.

Research papers study the factors that influence VTs for virtual team management models and those that have a significant impact on performance are chosen and, in turn, are mentioned in the literature. As seen in Figure 1 , this study has taken into account the different phases of the IPO model and its adaptation ( Gilson et al., 2015 ) along with the factors that are organized into Inputs (related to communication and trust), Processes (task-oriented and socio-emotional) and Outputs (performance).

Figure 1. Reference IPO model for analyzing VTs. Source: Based on authors.

As observed in VT models, communication is studied in relation to the characteristics of the tasks that will be developed and co-created in a distributed way.

Task Features

The interaction between task type and communication and its impact on team performance has been investigated in the literature ( Montoya-Weiss et al., 2001 ; Bell et al., 2002 ; Rico and Cohen, 2005 ). Because virtual teams rely heavily on communication technologies to coordinate their work, it is necessary to examine the relationship between the nature of the task and the effectiveness of communication that impacts team performance.

Software development projects are characterized by great uncertainty in terms of requirements and risk planning and followed by technological suitability until the project is completed. Task uncertainty has been conceptualized using various dimensions of task complexity in the literature. Some of the dimensions studied are task variety and task analyzability ( Daft and Lengel, 1986 ); variability ( de Ven et al., 1976 ); uniformity ( Mohr, 1971 ); predictability ( Galbraith, 1973 ); and complexity ( Duncan, 1972 ). The proposed model of information processing by Daft and Macintosh (1981) is comprehensive and captures the nature of virtual teamwork effectively through the dimensions of task variety and task analyzability.

As seen in the VTs models, trust is considered as leadership, cohesion and team empowerment. These 3 characteristics are described in more detail below:

One definition of leadership states that it is when a person gets other people to do something ( Kort, 2008 ). Leadership is an influential relationship between leaders and followers who attempt to make changes that benefit their mutual purposes ( Kort, 2008 ).

In VTs, transformational leadership seems to also arise from personality and communication factors ( Balthazard et al., 2009 ) and can increase performance, satisfaction ( Purvanova and Bono, 2009 ) and motivation ( Andressen et al., 2012 ).

Clearly, leadership is important for VTs. In one study ( Glückler and Schrott, 2007 ) it was found that communication influenced who emerged as a leader.

Glückler and Schrott (2007) found that communication behavior influenced who emerged as a leader. Similarly, leader–member exchange ( Goh and Wasko, 2012 ), perceptions of supportive leadership ( Schepers et al., 2011 ), leadership roles ( Konradt and Hoch, 2007 ) and cross-cultural leadership ( Sarker et al., 2009 ) have received attention, and other research has studied the impact of the type of recognition a leader uses to motivate workers ( Whitford and Moss, 2009 ).

Research on VT leadership has grown rapidly, with two popular areas being leadership behavior and traits ( Gilson et al., 2015 ). Here, the work has examined inspirational aspects ( Joshi et al., 2009 ) as well as transformational and transactional leaders ( Huang et al., 2010 ; David Strang, 2011 ). In VT, transformational leadership seems to be due to personality and communication factors ( Balthazard et al., 2009 ) and can increase performance, satisfaction ( Purvanova and Bono, 2009 ) and motivation ( Andressen et al., 2012 ).

Several studies have examined the interaction between leadership and virtuality, finding that team members are more satisfied with their team and leader and perceive that their leader is better able to decode messages when the leader is geographically distant from the team ( Henderson, 2008 ). Hoch and Kozlowski (2014) found that virtuality dampened the relationship between hierarchical leadership and performance while improving the relationship between structural supports and performance.

Clearly, leadership within VTs is important. As such, leaders can play a central role in how a VT works, particularly because they influence how a team deals with obstacles and how the team ultimately adapts to such challenges. This can be seen in articles on team adaptation research ( Baard et al., 2014 ).

Other research suggests that classic leadership styles are appropriate for a virtual team:

Democratic ( McBer and Company, 1980 ) and referee leadership styles ( Rashid and Dar, 1994 ) have some characteristics that are very suitable for a virtual team. One negative factor could be that many meetings are needed to reach consensus. In a virtual team, it is difficult and time-consuming to hold meetings for each decision.

Operational leadership ( McBer and Company, 1980 ) may be a good option because this leadership style gives team members clear roles and tasks. In addition, the leader makes the processes and structures very clear, so lack of communication will be reduced. A negative feature of this style of leadership for virtual teams might be that the contribution of the team members, and their responsibilities, might be a little less than the team members want.

Coaching leadership ( McBer and Company, 1980 ) fits virtual teams very well because it gives a lot of freedom to the team members, which means that they are also responsible for their work and results. Team members can set their own goals and therefore also progress personally while working in the virtual team. This leadership style, however, also has some difficulties. The processes, structures and roles of the team may not always be very clear because the leader allows team members to establish and use their own. Therefore, the success of the virtual team might suffer a little.

According to Salisbury et al. (2006) research into classical teams ( Lott and Lott, 1965 ; Hogg, 1987 ) suggest that the physical distance between members can be translated into a psychological distance between them. Following this line of reasoning ( Salisbury et al., 2006 ) the physical dispersion of the virtual team could inhibit cohesion. In addition, virtual team members may have different ideas about what cohesion is. In other words, the idea of cohesion, which is the communication between group members, is affected by the medium used to communicate. This is especially true given the ease with which users can exchange non-task related information in some environments. Clearly, the differences in communication patterns between virtual and onsite teams suggest that measures (such as PCS) which are used in one context cannot be directly employed in another without reevaluating them ( Boudreau et al., 2001 ).

Studies about group behavior ( Hogg and Tindale, 2001 ) consistently report that, in working groups, the members’ ability to get along with each other is critical for well-being and task performance. The importance of developing such intra-group cohesion has been shown to be especially relevant in cases where members don not know each other, such as in newly formed groups or when members are assigned to new project teams ( Griffin, 1997 ). The Symbolic Convergence Theory (SCT) proposed by Bormann (1983 , 1996) and tested by Bormann et al. (1994 , 1997) provides a rich theoretical framework for understanding group cohesion in traditional and technology-based teams.

One type of group cohesion is task cohesion and occurs when members stay together because they are strongly involved with the group’s tasks. Task cohesion will be greater if members identify with the group’s tasks and find them intrinsically rewarding and valuable.

Group cohesion for virtual teams with members working at different geographic locations, for different organizations, and even in different sectors of the economy, need effective communication and close coordination to achieve goals ( Powell et al., 2004 ).

The positive relationship between cohesion and trust in working teams has been confirmed in many investigations ( Evans and Dion, 1991 ; Simons and Peterson, 2000 ; Baltes et al., 2002 ; Powell et al., 2004 ; Spector, 2006 ; Lu, 2015 ).

Empowerment

Empowerment is favorable acknowledgment by the team leader and allows team members to participate in decision making. Empowerment makes the team member trust the leader, and when the leader asks for opinions and comments, he or she processes them and makes decisions based on the suggestions.

Some past studies ( Kirkman et al., 2004 ) indicate that teams can be empowered in four different ways, (a) power, which is the collective belief that a team can be effective, (b) significance, which is the extent to which team members care about their tasks, (c) autonomy, in which team members have freedom to make decisions; and (d) impact, the degree to which team members feel that their tasks make important contributions.

The impact of team empowerment on the performance of EVTs in 10 telecommunications companies in Islamabad was studied by Gondal and Khan (2008) . That study found that there is a positive relationship between team empowerment and team performance in telecommunications teams. Team performance includes the variables of cooperation, coordination, trust, cohesion, effort, mutual support, team conflict, job satisfaction and effectiveness in terms of quality.

Kirkman et al. (2004) also studied 35 sales and service teams at a high-tech firm and investigated the impact of team empowerment on team performance and the intermediary role of face-to-face interaction. They found that team empowerment is positively related to both constructs of virtual team performance, which are process improvement and customer satisfaction.

As indicated ( Kirkman et al., 2004 ) empowerment in a virtual team can be a substitute for the leadership tasks of a single team leader ( Kerr and Jermier, 1978 ). The behavior of the team members due to the leader’s empowerment is directly and positively related to trust. It is considered a confidence-building attribute. For empowerment, commitment is only reached when the team has a shared vision and honest and regular communication with the leader.

Models usually study the processes of tasks by investigating communication and the social-emotional processes of trust. The degree of virtuality and the interrelationship of tasks are also considered important for performance.

Communication

In mixed teams, where some members are at the same physical location and others are not, communication problems can also occur. Team members at the same physical place often communicate in a deeper way than with the distant members and this ends up causing friction between them and, therefore, damages the performance of the team ( Powell et al., 2004 ).

Communication, coordination and knowledge sharing are essential elements of action processes to predict the efficiency and effectiveness of the team ( Kock and Lynn, 2012 ).

Another study ( Peñarroja et al., 2013 ) found that as virtuality increased, team coordination declined, but this relationship was partially mediated by levels of trust.

Early research on VTs proposed that initial FtF meetings should help encourage performance ( Geber, 1995 ). Han et al. (2011) extended this line of reasoning to creativity and compared modes of initial communication to assess their impact.

Understanding how, why, and under what conditions trust develops remains a popular research topic. In part, the importance of trust can be attributed to results that suggest it positively affects the success of VTs ( Furumo, 2009 ).

For VTs, trust is influenced by communication behavior, timely responses, open communication, and feedback ( Henttonen and Blomqvist, 2005 ).

More recent findings suggest that rapid trust is likely to be established with early communication and a positive tone ( Coppola et al., 2004 ) and may influence performance by improving member confidence and subsequent trust ( Crisp and Jarvenpaa, 2013 ).

Other research has studied the impact of global VTs on trust development ( Lowry et al., 2010 ). Culturally heterogeneous teams (China and the United States) and homogeneous teams were compared and no significant differences were found in the trust between FtF teams and VTs ( Lowry et al., 2010 ).

Furthermore, in a longitudinal study of global VTs, Goh and Wasko (2012) found that when everyone’s actions were visible, trust was not a key factor in resource allocation.

Finally, in globally distributed teams, trust mitigated the negative effects of member diversity on performance ( Garrison et al., 2010 ).

Finally, aspects such as performance, quality of the product or service obtained and member satisfaction are relevant for the results. Of course, performance is the essential variable and is the usual interest of research into virtual teams.

Performance

Overall, research suggests that working in VTs can have a positive impact on effectiveness ( Kock and Lynn, 2012 ; Maynard et al., 2012 ), while others provide evidence suggesting that virtual working affects effectiveness negatively ( Cramton and Webber, 2005 ; Schweitzer and Duxbury, 2010 ).

A positive trend appears to be that work in this area is beginning to take advantage of ratings from outside the team ( Andressen et al., 2012 ; Cummings and Haas, 2012 ), as well as objective measures of team performance ( Rico and Cohen, 2005 ; Rapp et al., 2010 ).

In considering the elements of effectiveness, several researchers have examined the quality of the project ( Altschuller and Benbunan-Fich, 2010 ). This makes sense, since VTs are often used for special projects. In addition, the quality of the decisions made and the time taken to reach a decision have been studied and the findings are often that VTs need more time to make decisions ( Pridmore and Phillips-Wren, 2011 ).

Other studies find that VTs that set goals early in their life cycle showed greater cohesion and performance ( Brahm and Kunze, 2012 ).

Other work in this area also suggests that team motivation and performance can be improved by using mixed incentive rewards ( Bryant et al., 2009 ).

One study ( Kirkman et al., 2013 ) considered the impact of national diversity on performance and found a curvilinear (U-shaped) relationship moderated by both media richness and psychological safety.

Materials and Methods

The present study was carried out to understand the factors which influence the performance of VTs in a professional team that is used to using “agile” methodologies and virtual working.

A quantitative causal study using partial least squares (PLS) was performed using an online questionnaire, with a sample of 317 participants (Software Engineers).

Questionnaire and Measurement Scales

A quantitative research divided into the following blocks was designed and then carried out and the results were used to test the hypotheses that constitute the theoretical model. The details are shown in Table 1 .

Table 1. Variables of the proposed model.

Proposed Model

The proposed model that incorporated the hypothetical relationships is illustrated in Figure 2 .

Figure 2. Proposed model.

Research Hypotheses

The research hypotheses for the investigation of the factors that influence the performance of virtual teams are presented below.

Considerations of the Research Approach in the Hypotheses

Due to the quantitative approach chosen and by virtue of the delimiting nature of quantitative research, the hypotheses constitute the behavior that the variables or constructs are expected to show in the software development VT environment. Figure 2 shows the initial model. The hypotheses that are to be tested in this study are presented below:

H1: The characteristics of the tasks have a direct and positive influence on the communication of the virtual team members.

H2: The level of leadership of the members of the virtual team has a direct and positive influence on trust.

H3: The level of cohesion of the members of the virtual team has a direct and positive influence on trust.

H4: The level of empowerment of the members of the virtual team has a direct and positive influence on trust.

H5: Communication between virtual workers has a direct and positive influence on the confidence of the virtual team.

H6: Trust among virtual workers has a direct and positive influence on the performance of the virtual team.

H7: The level of communication between virtual workers has a direct and positive influence on the performance of the virtual team.

Hypothesis Research Scope Considerations

The correlational scope used to find the relationships between variables that give an answer to a problem means that without proving these relationships there could be a causal link between the variables. Figure 2 shows the constructs of the hypotheses in the study model.

Additionally, it is important to reiterate, that the VT performance construct is based on the relationships with the aggregate constructs Communication (h9) and Trust (h10) which in turn are expected to have a strong relationship between them and this will be tested in the research (h7 and h8). Then, the latent variable called communication has the constructs of cultural diversity (h1), the characteristics of the tasks (h2), as well as the distribution index (h3). Finally, the variables leadership (h4), cohesion (h5), and empowerment (h6) are used to find the latent variable trust.

The model used for the research hypotheses, its variables and its relationships are described in the literature review section.

Sampling and Data Collection

1,200 software engineers with experience in programming with Agile methodology (which involves co-creation and collaboration in virtual teams) and who had graduated in the last 10 years, were directly invited to take part in the survey. 317 responses were collected.

The study was designed based on robust studies previously applied to telework and virtual teams in globally distributed teams for 20 years and after a robust literature review on the most relevant factors affecting the performance of these teams.

The study was applied at a privileged moment 3 months after the official declaration of the Covid pandemic19 by The World Health Organization.

The population taken into account for this study is considered stable because they were graduates of accredited engineering degrees from universities recognized in Costa Rica for their training in software development over the past 20 years and related colleagues.

Parallel to this study, a control study was conducted on another more heterogeneous population of professionals who in many cases had to start from scratch in the form of teleworking or virtual teams. This helped to understand and further refine the proposed model.

Demographic Details

As can be seen in Table 2 , the results found for the demographic features of the 317 members of virtual teams that use agile methodologies for the development of their projects are tabulated.

Table 2. Demographic details.

For gender, it is normal that in Software Engineering (SE) there is a higher proportion of men (81%) than women (19%). For age, it should be noted that 65% of those who responded to the questionnaire about virtual teams of SE were digital natives (born after the 1990s).

For the time spent working in VTs, almost 90% of the young members of SE VTs had joined in the last 5 years, which is consistent with handling agile methodologies and virtual teams in this profession.

The proportion of leaders is approximately 30% of the group and members 70%. In the SE VTs it was notable that 58% of the members have also been project leaders before, due to the dynamics of the Agile methodology and value co-creation. The diversity of membership in organizations shows that the members from SE VTs were 25% of the sample group and the members of VTs from other professions (OP) were 5% due to their recent incorporation into this way of working.

The members of SE VTs (68%) were very interested in continuing working in VTs in a new post-Covid19 normality.

Important Findings

It is clear that the objective of the work is to analyze the determinants of performance in virtual teams in a time of pandemic, where conditions forced the vast majority of workers to develop their work within their homes remotely, forming virtual teams in which they already participated or had to organize in this way. With this objective, a survey has been conducted among software engineers and they have specified a structural equation model to analyze the relationship between different inputs and processes in the output. The results obtained show the relevance of communication and confidence in the performance of virtual teams. But before reviewing the complete model it is important to mention some important findings:

– The participants in this study were professionals in the area of computer science, dedicated to the development of software. Mainly digital natives with experience in VTs, people with ages between 18 and 29 years (64.98%) and digital migrants between 30 and 39 years (18.93%) with high mastery of information and communication technologies ICTs. In general, they consider that virtual teamwork is an excellent way to develop their work in the world of technology. It is part of their profession. In the worst case, some engineers maintain a neutral stance toward the issue of virtual teamwork. Under normal conditions they have worked in virtual mixed mode and face to face, so under 100% pandemic conditions, they really didn’t have much of an adjustment problem, because they were already doing it before. Even when asked about the future, a high number (68.45%) see themselves working in virtual teams and 28.71% in mixed mode.

– The professionals interviewed in many cases have indicated that communication in virtual teams is a factor that must be improved in frequency and quality because they feel that the initial instructions are not enough. Others take communication as a natural factor, regardless of whether the communication is virtual or face to face. Finally others indicate that communication in the virtual team is better with the good use of collaborative tools.

– Trust is a very important factor in the study, because it allows employees to perform their tasks at a distance in a better way, as long as their tasks are measured by objectives. Too many controls throughout the work process make the virtual collaborator feel watched and that he is being evaluated negatively.

– Regarding the geographical distribution, software engineers agree with professionals from other areas in that it saves them time and money and due to the intensive and natural use of ICT in their profession, the physical distance was not relevant to achieve the objectives.

– Regarding the cultural diversity in this study, being regional, the interviewees gave positive answers because the cultural differences did not influence their performance in the software development projects that have in common in a standardized way the computational language and the technological architectures.

– About the distribution of tasks, to be developed projects with agile methodologies, the specifications of functional and technical requirements are very clear from the beginning and also are clarified or refined in time with the coordination, co-creation and collaborative work, so engineers have clear what their tasks are throughout the process. As for the Interdependence of tasks there was no significant finding at the level of software development operations. It is possible that this is due to the fact that software projects are structured at the level of by-products and tasks in an orderly manner.

– By using agile methodologies to develop work with virtual teams and distributing tasks among members early on, empowering each member individually and in relation to others has been vital in software projects. Depending on the level of experience and individual skills, empowerment is increasingly important in virtuality.

– Leadership is a fundamental issue, which directly influences the confidence of virtual collaborators. In this study the members of the virtual teams gave it a moderate importance because of the work methodology and the mixed experience: virtual and face to face, the works are done in a collaborative and very horizontal way. Additionally, 58.04% indicated that they had already led some software development in this modality in the past.

– The virtual team software development has made the collaborators work longer interacting through the ICTs, fighting to achieve common objectives. This has made that the cohesion between them has increased at work level.

Sample Frame

A random database of 1,000 software engineers graduated in the last 20 years from accredited software engineering or systems engineering careers at universities in Costa Rica, a country with a tradition and recognition of many years of software development for the region of Central and North America (mainly United States), was taken into account.

The survey was applied from May to July 2020, in the midst of the Covid19 pandemic, using an email invitation for respondents to fill out an electronic survey instrument using the Google Forms platform with 65 items.

Limitations

There are many factors previously studied that influence in one way or another the performance of VTs, but at the level of the proposed model they cannot all be included because they have shown that their influence has not been very strong or because the type of population that was chosen for this specific study was not relevant. For example, a limitation of this study is that the dimension of rewards was not considered, since in recent similar studies they have not shown significant relationships ( Tan et al., 2019 ).

A second limitation that could be considered, is related to the fact that, the respondents belong to different institutional environments, regularly projects of 5–10 members, in medium sized software development companies. In this sense, it is common that they use agile methodology as the project organization standard, which compensates for the differences in size of the parent organization, type of products developed, the member’s country of origin and the country of origin of the final client.

The cultural diversity that has been extensively studied in virtual teams, in this study was included in the survey but its results did not show a significant influence because the software development projects were usually regional and associated with the same continent and time zones with few differences.

Analysis of Results

Results for the measurement model.

The measurement model was tested for internal reliability, convergent validity and discriminant validity. The internal reliability was evaluated using Cronbach’s alpha which needs a value of at least 0.70 for acceptable internal consistency ( Hair et al., 2013 ). Causality was analyzed using indicator loadings. Composite reliability was also used to investigate causality ( Werts et al., 1974 ). All the constructs had internal consistency as all the values for Cronbach’s alpha were higher than 0.7 ( Fornell and Larcker, 1981 ; Bagozzi and Yi, 1988 ; Hair et al., 2011 ). Fornell and Larcker (1981) used the Average Variance Extracted (AVE) to assess convergent validity, and stated that an acceptable value for this factor is AVE ≥ 0.50.

Table 3 shows the element loads, Cronbach’s alpha and AVE which were found for the constructs. Values for Cronbach’s alpha ranged from 0.914 to 0.709, which is higher than the recommended level of 0.70 and therefore indicates strong internal reliability for the constructs. The composite reliability ranged between 0.946 and 0.837 and the AVE ranged between 0.632 and 0.853, which are higher than the recommended levels. The conditions for convergent validity were therefore met. The discriminant validity was calculated with the square root of the AVE and the cross-loading matrix. For satisfactory discriminant validity, the square root of the AVE of a construct should be greater than the correlation with other constructs ( Fornell and Larcker, 1981 ).

Table 3. Reliability, validity of the constructs, Fornell–Larcker criterion and HTMT.

These researchers carried out simulation studies to demonstrate that a lack of discriminant validity is better detected by means of another technique called the heterotrait-monotrait ratio (HTMT), which they had discovered earlier. All the HTMT ratios for each pair of factors was <0.90.

Results for the Structural Models

The structural model was built from the different relationships between the constructs. The hypotheses for the study were tested by analyzing the relationships between the different constructs in the model to see if they were supported ( Chin and Newsted, 1999 ; Reinartz et al., 2009 ).

The variance is found from the values for the reflective indicators of the constructs ( Barclay et al., 1995 ; Chin, 2010 ). This was found numerically by calculating the values of R 2 , which is a measure of the amount of variance for the construct in the model. The bootstrap method was used to test the hypotheses. The detailed results (path coefficient, β, and t -statistic) are summarized in Table 4 and Figure 3 .

Table 4. Results of hypothesis: path coefficients and statistical significance.

Figure 3. Final model. *** p < 0.001 [ t (0.001; 499) = 3.106644601].

The measurements for approximate adjustments of the model ( Henseler et al., 2016 ; Henseler, 2017 ) are given by the Standardized Root Mean Square Residual (SRMR) value ( Hu and Bentler, 1998 ) which measures the difference between the observed correlation matrix and the implied correlation matrix of the model. SRMR shows the average magnitude of these differences.

A low value of SRMR means that the fit is better. In our case SRMR = 0.055, which was within the recommendations for a model with a good fit. A good fit is considered to be shown with a value of SRMR < 0.08 ( Hu and Bentler, 1998 ).

The following conclusions were made from the values for R 2 (see Table 5 and Figure 3 ) found in the research by Chin (1998) and show that 0.67 = “Substantial,” 0.33 = “Moderate,” and 0.19 = “Weak.” The result obtained for the main dependent variable of the model, Performance (PER) R 2 = 48.4% was moderate and the rest of constructs, Trust R 2 = 74.2% and Communication (COM) R 2 = 33.3%.

Table 5. R 2 results.

This value shows that this model is “substantially” applicable to the performance of virtual teams. Please note that the variables that are not endogenous do not have a value for R 2 .

The results obtained for the proposed model have found that the performance of virtual teams is moderately justified by the determinants as R 2 = 48.4%. However, the value obtained for Trust ( R 2 = 74.2%) should be noted as it means that the variance of this construct explains to a high percentage, aspects such as the confidence of the virtual team. This is essential to improve the co-creation of software development teams.

This study confirmed that the most significant variable for the performance of the EVT is Trust (H6), since this variable has the strongest influence on the dependent variable Performance. It also has a very high predictive capacity as the determination coefficient is high (β = 0.684; t = 14.281).

These results coincide with other recent findings that confirm that Trust can influence performance by improving member confidence and the subsequent trust ( Crisp and Jarvenpaa, 2013 ). So when everyone’s actions are visible, trust was not a key factor in resource allocation ( Goh and Wasko, 2012 ).

The next most important variable in the model is Task features (H1). Virtual teams rely heavily on communication technologies to coordinate their work, so the relationship between the nature of the task and the effectiveness of communication was studied in order to find its subsequent impact on team performance. Therefore, one of the determinants was the characteristics of the tasks and the positive influence on the communication of the members of the virtual team. The result was positive with a confidence level of 99.9%. Therefore, H1 was supported (β = 0.577; t = 13.842). These results amply confirm that great uncertainty about the requirements and the risk planning, followed by the technological suitability of the projects, are key to communication.

Our study also confirmed that the level of empowerment of the members of the virtual teams was also found to have a significant effect on Trust (H4). This result showed that Empowerment positively promotes and increases the confidence of a virtual team (β = 0.348; t = 7.086).

These results coincide with previous work ( Gondal and Khan, 2008 ) that measured the impact of team empowerment on VT performance and demonstrated that there is a positive relationship between team empowerment and team performance in virtual teams. Our findings go further and state that this is achieved with Trust. As with other studies ( Kirkman et al., 2004 ), empowerment in a virtual team can work as an alternative to leadership. Thus, the activities that are normally done by a team leader can be carried out by the members ( Kerr and Jermier, 1978 ) by contributing with co-creation. This behavior of the team members because of the empowerment of the team members by the leader has a direct and positive relationship with trust. It is considered a confidence-building attribute. In empowerment, commitment is only reached when the team has a shared vision and honest and regular communication with the leader.

The relationship with the next highest confidence level for trust in the virtual teams was H3: the level of cohesion of the members of the virtual teams (β = 0.366; t = 6.725). This finding shows that the ability of the members of a virtual team to get along with each other is critical to the well-being of the group and task performance. These findings are consistent with previous work ( Evans and Dion, 1991 ; Simons and Peterson, 2000 ; Baltes et al., 2002 ; Powell et al., 2004 ; Spector, 2006 ; Lu, 2015 ).

Therefore, it will be very important for software development companies to implement intragroup cohesion measures. These findings are consistent with other work ( Griffin, 1997 ). Similarly, managers could implement economic incentives that support their software developers to be strongly involved with the group’s tasks. Task cohesion will be greater if members identify with the group’s tasks and find them intrinsically rewarding and valuable.

In the current context with the Covid-19 pandemic, this cohesion has been highly questioned. Let’s not forget that the isolation measures decreed by many governments have made it difficult to deal with aspects such as different geographical locations, belonging to different organizations, and different sectors of the economy. This has made effective communication and close coordination difficult. However, the results reaffirm the theories already shown ( Powell et al., 2004 ).

One of the factors is the level of leadership of the members of the virtual teams (H2). The results showed that this had a direct and positive influence on Trust (β = 0.138; t = 3.209). Clearly, leadership in VTs is important. The results obtained coincide with the study by Baard et al. (2014) and show that the role of leaders is important for working in a VT, especially because leaders influence the way a team faces obstacles and the way the team ultimately adapts to such challenges, which is very important for the confidence generated for the future.

Therefore, the leader of a virtual team must use a style that generates Trust as a mediating factor in the indirect effect that this has on Performance.

The Communication between virtual workers has a direct and positive influence on the confidence of the virtual team and was supported (β = 0.160; t = 3.741) with a confidence level of 99.9%. Our study does support this hypothesis and agrees with Peñarroja et al. (2013) , who found that as virtuality increased, team coordination declined, but this relationship was partially mediated by levels of Trust. In addition, as can be seen in the results, it is the least strongly supported hypothesis.

H7, the level of communication between virtual workers has a direct and positive influence on the performance of the virtual team, was not supported (β = 0.019; t = 0.353). This outcome appears to be conditioned by the very high levels of virtuality that have been reached during the containment measures decreed by governments at the start of the Covid-19 pandemic and, as stated above, clearly demonstrate that communication influences trust only through trust.

This result reaffirms the role of trust-building in achieving the highest performance of the virtual team and allows us to conclude that the confidence of all members in the virtual team is key to success in software development.

The proposed model based on the IPO adaptation ( Gilson et al., 2015 ) has been largely validated using a PLS-SEM analysis. Therefore, software companies can use it as a theoretical framework when preparing their human resources and Virtual Teams management policies.

The important role of Trust as a basis for most of the variables of the model shows that it should be considered as one of the most important and relevant variables, especially because of the increase in virtualization and teleworking during the Covid-19 pandemic. Companies must give greater importance to Trust and take into account that all measures which strengthen leadership, communication, cohesion or the configuration of task characteristics must be designed considering the trust generated. It is interesting to note that economic incentives can help with group cohesion and policies improve empowerment. One such incentive could be skills training for group members. These measures may become more important than leadership in the coming years, given the results found during the pandemic.

Finally, this study was completed with software developers who use agile methodologies and who have good IT skills. The results, therefore, show that the increased virtuality brought about by the pandemic can be an opportunity to innovate in communication to influence performance.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author Contributions

VG-A undertook the research, collected the data, and prepared the initial manuscript. PP-S completed, revised, and finalized the manuscript, and participated in the preparation of the manuscript. MA-C provided the intellectual input and analyzed the data. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords : global software development, COVID-19, virtual teams, determinants of performance, PLS-SEM

Citation: Garro-Abarca V, Palos-Sanchez P and Aguayo-Camacho M (2021) Virtual Teams in Times of Pandemic: Factors That Influence Performance. Front. Psychol. 12:624637. doi: 10.3389/fpsyg.2021.624637

Received: 31 October 2020; Accepted: 18 January 2021; Published: 17 February 2021.

Reviewed by:

Copyright © 2021 Garro-Abarca, Palos-Sanchez and Aguayo-Camacho. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Pedro Palos-Sanchez, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Challenges and barriers in virtual teams: a literature review

• Research Article
• Published: 20 May 2020
• Volume 2 , article number  1096 , ( 2020 )

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• Sarah Morrison-Smith   ORCID: orcid.org/0000-0002-4959-807X 1 &
• Jaime Ruiz 2  

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Virtual teams (i.e., geographically distributed collaborations that rely on technology to communicate and cooperate) are central to maintaining our increasingly globalized social and economic infrastructure. “Global Virtual Teams” that include members from around the world are the most extreme example and are growing in prevalence (Scott and Wildman in Culture, communication, and conflict: a review of the global virtual team literature, Springer, New York, 2015). There has been a multitude of studies examining the difficulties faced by collaborations and use of technology in various narrow contexts. However, there has been little work in examining the challenges faced by virtual teams and their use of technology to mitigate issues. To address this issue, a literature review was performed to highlight the collaboration challenges experienced by virtual teams and existing mitigation strategies. In this review, a well-planned search strategy was utilized to identify a total of 255 relevant studies, primarily focusing on technology use. The physical factors relating to distance are tightly coupled with the cognitive, social, and emotional challenges faced by virtual teams. However, based on research topics in the selected studies, we separate challenges as belonging to five categories: geographical distance, temporal distance, perceived distance, the configuration of dispersed teams, and diversity of workers. In addition, findings from this literature review expose opportunities for research, such as resolving discrepancies regarding the effect of tightly coupled work on collaboration and the effect of temporal dispersion on coordination costs. Finally, we use these results to discuss opportunities and implications for designing groupware that better support collaborative tasks in virtual teams.

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1 Introduction

Virtual teams (i.e., geographically distributed collaborations that rely on technology to communicate and cooperate) have several potentially beneficial aspects that aid productivity. Much like collaboration in co-located teams, collaboration in virtual teams refers to synchronous and asynchronous interactions and tasks to achieve common goals. The use of virtual teams allows organizations to enroll key specialists, regardless of their physical location [ 106 , 151 ]. This allows organizations to optimize teams by using only the best talent available [ 63 , 136 ]. In theory, virtual teams also reduce the need for travelling between sites, which should reduce costs in terms of time, money, and stress [ 196 ]. It was estimated that by 2016, more than 85 % of working professionals were in some form of virtual team [ 235 ]. This implies that, as a result, virtual teams have become vital to maintaining our increasingly globalized social and economic infrastructure.

Similar to co-located teams, virtual teams participate in a variety of collaborative activities such as formal and informal meetings using technology like video conferencing (e.g., Zoom [ 121 ] and Skype [ 175 ]) and text (e.g., Slack [ 232 ] and Microsoft Teams [ 176 ]), file transfer, and application sharing [ 191 ]. As a result, virtual teams are experiencing difficulties collaborating that are making it difficult for them to be as successful as co-located teams [ 64 , 151 , 191 ]. As a result, virtual teams spend substantial time and money to relocate team members for specific projects to avoid the hindrances to teamwork associated with distance [ 231 , 257 ]. It is therefore important to develop technology that can better support virtual teams, reducing the need for costly re-locations and mitigating the problems that arise when relocation is not a viable solution.

Despite previous research examining the difficulties faced by collaborations and use of technology in specific contexts, such as distributed software development, there has been little work in examining the challenges faced by all virtual teams and their use of technology to mitigate issues. This understanding is vital to the development and utilization of technology to support virtual teams. Thus, this paper has two goals: (1) to elucidate the factors and challenges that hinder collaboration in virtual teams and (2) provide recommendations for designing groupware to better support collaboration in virtual teams, while also identifying opportunities for the Human–Computer Interaction (HCI) community to design this technology.

To achieve our goals, a Literature Review (LR) was performed with a well-planned search strategy that identified a total of 255 relevant studies, primarily focusing on technology use. Based on the selected studies, we categorized challenges as being related to: geographical distance, temporal distance, perceived distance, the configuration of dispersed teams, and diversity of workers. In addition, results from this LR identify opportunities for research, such as resolving discrepancies regarding the effect of tightly coupled work on collaboration, the effect of temporal dispersion on coordination costs, and whether virtual teams encounter more work-culture related problems than co-located teams. From the synthesis of these papers, we present four design implications for designing groupware that better support collaborative tasks in virtual teams.

This literature review explores the factors and challenges associated with collaboration in virtual teams. This paper begins with a review of related LRs in the domain of collaboration in Sect.  2 and progresses to a description of the method used to conduct the LR in Sect.  3 . Sections  5 and 6 explore issues related to distance and other contributing factors, respectively. Next, in Sect.  7 , findings from Sects. 5 and 6 are summarized, leading to Sect.  8 which completes the LR by presenting a set of four design implications for the development of groupware that supports collaboration in virtual teams.

2 Related work

Prior work includes eight systematic literature reviews surveying various topics related to distance collaboration. These topics fall into two categories: investigations of virtual teams in the domain of distributed software development (DSD) and explorations of the factors that influence collaboration in broader contexts.

Research into the challenges faced in DSD have resulted in determination of the factors associated with the relationship between distribution, coordination, and team performance that are the most commonly studied in software development, namely dimensions of dispersion (e.g., geographical, temporal, organizational, work process, and cultural dispersion) and coordination mechanisms (e.g., organic or social coordination and mechanistic or virtual coordination) [ 183 ]. Several challenges (e.g., including geographical, temporal, cultural, and linguistic dispersion [ 146 , 185 ]) and best practices or practical solutions (e.g., agile methods, test-driven development [ 146 ], frequent site visits and face-to-face meetings [ 185 , 233 ]) have been identified for traditional DSD teams [ 185 ] and teams that use a ‘follow-the-sun’ approach (i.e., where teams hand off work at the end of the day in one time-zone to workers beginning their day in another) [ 146 ]. Additional work identified opportunities for future research, such as addressing challenges present in multi-organizational software projects and supporting the development of coordination needs and methods over the course of a project [ 184 ]. This category of research also includes a study that classified empirical studies in DSD [ 64 ], revealing that communication warrants further exploration to better support awareness in this context [ 239 ].

These studies are informative and discuss several of the challenges that appear later in this LR (e.g., geographical, temporal, cultural, and linguistic dispersion). However, it is not guaranteed that the findings from the DSD studies with regards to these dimensions directly translate to collaboration in another context. In contrast, this paper examines distance collaboration in all virtual teams.

Other studies have studied the factors affecting collaboration in general. Mattessich and Monsey identified 19 factors necessary for successful collaboration, including the ability to compromise, mutual respect and trust, and flexibility [ 167 ]. Similarly, Patel et al. [ 201 ] developed a framework based on the categorization of seven factors related to collaboration (e.g., context, support, tasks, interaction processes, teams, individuals, and overarching factors) for use in collaborative engineering projects in the automotive, aerospace, and construction sectors.

In contrast to the results of the DSD studies, these findings apply to a broad range of contexts. However, since these literature reviews primarily focus on co-located collaboration, it is difficult to discern how the factors identified by these studies influence virtual teams. This paper differs by focusing only on virtual teams.

Relevant papers were extracted for LR using the guidelines proposed by Kitchenham and Charters [ 138 ] for performing Systematic Literature Reviews in software engineering, with the adjustments recommended by Kitchenham and Brereton [ 137 ]. These guidelines divide the review process into three steps:

Planning the review In this step, the research questions and review protocol are defined. This will be discussed in the remainder of Sect.  3 .

Conducting the review This step focuses on executing the review protocol created in the previous step. This will also be discussed in Sect.  3 .

Reporting the review This final step documents, validates, and reports the results of the review. This will be the subject of Sects. 5 and 6 .

3.1 Planning the review

This subsection will focus on developing the list of research questions used to generate the list of keywords for extracting papers and specify the search methodology.

3.1.1 Specifying research questions

The first stage of this literature review began by defining research questions using the Goal-Question-Metric approach described by Van Solingen et al. [ 258 ], which systematically organizes measurement programs. This model specifies the purpose, object, issue, and viewpoint that comprise a goal, which is then distilled into research questions and used to create metrics for answering those questions. The goal of this LR is:

Purpose Understand and characterize

Issue The challenges

Object Related to collaboration

Viewpoint Faced by workers in virtual teams

Using this goal, these research questions were derived:

What are the factors and challenges that impact distance collaboration?

What factors specific to distance cause issues?

What other factors contribute to these issues?

How can we design technology for supporting virtual teams?

The purpose of asking question 1 is to outline previous research investigating collaboration challenges. The expected outcome will be a comprehensive view of challenges affecting collaborations and identification of gaps or areas warranting future exploration. Research Question 1a will be the topic of Sect.  5 while Research Question 1b will be explored in Sect.  6 . Research Question 2, however, focuses on the development of technology for supporting collaboration. The answers to this question will yield an overview of design implications for the creation of groupware, which will be discussed in Sect.  8 .

3.1.2 Developing and executing the search strategy

The research questions listed above were used to identify keywords to use as search terms. For example, for the sub-question ‘ What factors can be attributed to distance ?’ the following keywords were selected: collaboration , distance , challenge ; in addition, synonyms and related words were also searched (e.g., geography, teamwork). This search can be described by the following boolean search query:

(collaboration OR teamwork OR CSCW) AND (challenge OR problem) AND (distance OR geography)

Our search methodology used multiple searches as terms were either exhausted or identified by collected papers. The generated search terms were used to conduct searches using Google Scholar since this search engine conducts a meta-search that returns results from several paper repositories (such as Science Direct, ResearchGate, Academia.edu, and the ACM digital library). During the review, it became apparent that after the first 8–9 pages of results, we reached concept saturation. As a result, we limited our search to the first 10 pages for a total of 1200 potential sources.

In addition, collected papers were used to generate additional searches via a ‘snowballing’ effect [ 26 , 249 ]. Specifically, collected papers were used to generate additional keywords, identify additional papers through the bibliography, identify newer papers that cited them, and identify authors who had written important papers published in relevant conferences. These included papers published in the ACM conference on Computer-Supported Collaborative Work (CSCW) and the ACM International Conference on Supporting Group Work (GROUP). These authors were searched for using the identified search engines, and all their papers were evaluated for inclusion. In addition, other researchers proposed sources that were used to boost paper extraction. These additional methods were used because prior work by Greehalgh and Peacock [ 91 ] found that less efficient methods like snowballing are likely to identify important sources that would otherwise be missed, since predefined protocol driven search strategies cannot solely be relied on.

3.1.3 Inclusion and exclusion criteria

The first ten pages of results from Google Scholar were reviewed since occasionally keywords resulted in a high amount of potential papers. All papers were reviewed from searches resulting in fewer than ten pages of results. As part of our search methodology, we utilized several inclusion and exclusion criteria to filter the collected papers from the potential papers found using the systematic search and snowballing. These inclusion and exclusion factors are listed in Table 1 . Figure 1 shows the number of identified papers that met the inclusion criteria across 5-year periods.

Distribution of cited papers across time

3.1.4 Paper categorization

To facilitate analysis, the papers identified as part of the LR, shown in Fig.  1 , were further categorized by study type and contribution. Tables  2 ,  3 ,  4 ,  5 ,  6 ,  7 and  8 in the “ Appendix ” contain each paper organized by these categories.

4 Factors affecting virtual teams

Virtual teams are affected by physical factors such as geographic distance, in addition to temporal and perceive distance, which are time-based and cognitive respectively. These factors are tightly coupled with social and emotional factors, including trust, motivation, and conflicts. Based on the papers in this literature review, we separate these factors into the categories of distance factors, (which include geographical (physical), temporal, and perceived distance) and contributing factors that are driven by distance (including the nature of the work, the presence or need for explicit management, and group composition). Each category correlates with a set of challenges that greatly affect virtual teams. Distance categories and their associated challenges are discussed in Sect.  5 to answer Research Question 1a: what factors specific to distance cause challenges that impact distance collaboration? Contributing factors are discussed later in Sect.  6 .

5 Distance factors

Distance can be categorized as being primarily geographical, temporal, or perceived. Each category correlates with a set of challenges that greatly affect virtual teams. Distance categories and their associated challenges are discussed in the following sections to answer Research Question 1a: what factors specific to distance cause challenges that impact distance collaboration?

5.1 Geographical distance

Geographical distance has been defined as a measurement of the amount of work needed for a worker to visit a collaborator at that collaborator’s place of work, rather than the physical distance between the two collaborators [ 2 ]. Thus, two physically distant locations could be considered geographically close if they have regular direct flights. Even a distance as small as 30 meters has been shown to have a profound influence on communication between collaborators [ 4 ].

Furthermore, geographical distance is well known to pose challenges for virtual teams [ 191 ]. Olson and Olson explored these challenges at length in 2000 [ 191 ] and 2006 [ 193 ]. Their first work compared remote and co-located work through an analysis of more than ten years of laboratory and field research examining synchronous collaborations [ 191 ]. The 2006 paper presented a follow-up study that synthesized other prior work [ 78 , 190 ] to expand their 2000 contribution [ 193 ]. Findings from both studies identified the following ten challenges that hinder distance work:

Awareness of colleagues and their context

Motivational sense of presence of others

Trust is more difficult to establish

The level of technical competence of the team members

The level of technical infrastructure

Nature of work

Explicit management

Common ground

The competitive/cooperative culture

Alignment of incentives and goals

Challenges 1–5 will be discussed in this section while Challenges 6–10 will be topics of interest later in Sect.  6 .

5.1.1 Motivation and awareness in distributed collaborations

The motivational sense of the presence of others has well established ‘social facilitation’ effects, particularly the observation that people tend to work harder when they are not alone [ 193 ]. However, these effects are harder to find and cultivate in remote work, which poses an additional challenge to collaboration. In a similar vein, the difficulties associated with maintaining awareness of collaborators’ work progress at remote locations without the ability to casually ‘look over their shoulder’ is a significant challenge to collaboration [ 193 ]. The cause of these problems is likely because co-located workers have more opportunities for casual encounters and unplanned conversations [ 144 ], which boosts awareness. Similarly, distance prevents the informal visual observations necessary for maintaining awareness [ 8 ]. This is important since workers use the presence of specific teammates in a shared space to guide their work and prefer to be aware of who is sharing their work space [ 71 ]. Furthermore, the inability of virtual team members to observe each other’s actual effort tends to lead to a greater reliance on perceptions and assumptions that could be both biased and erroneously negative [ 206 ]. In addition to this, in situations where disengagement is not apparent, virtual team’s reliance on technology to communicate allows team members to disengage from the team due to decreased social impact [ 16 ]. Isolation can have an effect as well—when members of a virtual team become more isolated, their contributions and participation with the team decrease [ 32 ].

The importance of awareness in collaboration is discussed at length by Dourish and Bellotti [ 62 ], who investigate awareness through a case study examining ShrEdit [ 171 ], a text editor that supports multiple users synchronously. In this paper, awareness is defined as ‘an understanding of the activities of others, which provides a context for your own activity’ [ 62 ]. Dourish and Bellotti further stipulate that this context is necessary for guaranteeing that each person’s contributions are compatible with the group’s collective activity and plays a critical role in assessing individual actions in accordance with the group’s goals and progress. This context further allows individuals to avoid duplication of work. Collaborative work is significantly delayed without such awareness [ 193 ]. Moreover, awareness is a mandatory requirement for coordinating group activities, independent of the domain [ 62 ].

Many computer-based technologies have been developed to assist distance workers in maintaining awareness of their collaborators. Research suggests that the adoption of tools that allow members of virtual teams about the timing of each other’s contributions and activities may improve team coordination and learning [ 18 ]. Systems that provide real-time visual feedback about the behaviors of team members can be used as tools to mitigate various sources of “process-loss” in teams (e.g., team effort) [ 89 ]. Some early systems (e.g., [ 17 , 81 , 160 ]) were designed to feature computer-integrated audiovisual links between locations that were perpetually open, the idea being that providing unrestricted face-to-face communication and a ‘media space’ would facilitate collaboration as though the workers were in the same physical space. Since then, a number of modern systems (e.g., [ 153 , 197 ]) have been developed. For example, Glikson et al. [ 89 ] developed an effort visualization tool that calculated effort based on the number of keystrokes that team members made in a task collaboration space. They found that the visualization tool increased team effort and improved performance in teams that had a low proportion of highly conscientious members [ 89 ]. This effect did not hold true for teams with a high proportion of highly conscientious members. See the work of [ 154 ] for a more comprehensive review of awareness-supporting technology.

The concept of awareness as a direction for research has been criticized. In 2002, Schmidt argued that the term awareness was ‘ambiguous and unsatisfactory (p. 2)’ due to its exceptionally wide range of diverse applications and tendency to be paired with an adjective (e.g., ‘passive awareness’ [ 62 ]) in an attempt to lend some specificity. Instead, Schmidt recommended that researchers pursue more explicit, ‘researchable questions (p. 10)’ rather than focus on the enigmatic concept of awareness. This is more than a call to change terminology, but rather a fundamental shift in the way that research in this area is approached. Despite this recommendation, the awareness approach is still a commonly explored area [ 7 , 134 ], indicating disagreement within the community that has yet to be resolved, presenting a research opportunity.

5.1.2 Establishing trust

Throughout the relevant studies canvassed in this paper, trust has been defined in a multitude of ways. Cummings and Bromily [ 53 ] define trust within a collaboration as the worker’s belief that their team (a) ‘makes a good-faith effort to behave in accordance with any commitments both explicit or implicit, (b) is honest in whatever negotiations preceded such commitments, and (c) does not take excessive advantage of another even when the opportunity is available’. Pinjani and Palvia [ 208 ], in contrast, have a simpler definition of trust as the ‘level of confidence exercised among team members,’ and Choi and Cho [ 42 ] describe interpersonal trustworthiness as characterized by ability, benevolence, integrity, and goal congruence. Trust in the business literature is described as a person’s psychological state which indicates the person’s expectation that their team member will not act in a self-interested manner at the expense of the person’s welfare, which increases readiness to accept vulnerability [ 44 ]. Cho redefines this as a person’s believe in the beneficial actions of another even with the other is given the opportunity to act in self-interest [ 41 ]. Along with this, De Jong et al defines trust as ‘a shared and aggregate perception of trust that team members have for each other’ [ 59 ]. Lastly, Meyerson et al. [ 174 ] describe a specific type of trust, known as ‘swift trust’, which occurs in temporary organizations. The commonalities among these definitions include a perception that trust involves the belief that a collaborator will act in a beneficent manner as opposed to self-interest, acts in good-faith to honor commitments.

According to prior work [ 23 , 42 ], trust is the key variable that is crucial for all aspects of collaboration This includes team effectiveness, since trust determines whether team members ask each other for help, share feedback, and discuss issues and conflicts [ 23 ]. Team trust has a significant effect on team performance [ 59 ] and can be considered the ‘glue’ that holds collaborations together [ 48 ]. In fact, building mutual trust and personal knowledge about collaborators is more important to a good collaboration than resolving technical issues [ 250 ]. Furthermore, trust is particularly important in virtual teams since interactions on computer-mediated communication (CMC) technologies tend to be superficial (i.e., lacking contextual cues such as facial expressions and tone of voice) [ 38 , 155 , 267 ], impersonal, and less certain [ 155 ].

Trust is linked to positive aspects of collaboration. For example, commitment to the team and project is greatly influenced by trust [ 28 ]. Trust can also improve collaboration infrastructure [ 10 ] and is also crucial for the occurrence of normative actions [ 48 ]. Maurping and Agarwal [ 165 ] found that building trust early on in a virtual collaboration plays a critical role in developing adequate group functioning and the ability to manage social activities. In addition, virtual teams that develop trust early may notice information confirming the competence of their team members and may not notice contradicting evidence [ 273 ]. As a result of their early development of trust, members of these teams also gain the confidence to engage in normative actions that sustain both trust and later performance [ 48 ]. While some research has found that the relationship between early trust and performance is stronger in highly virtual teams than in less virtual teams [ 163 ], whether the performance actually improves is up for debate. Some prior work [ 128 ] reports positive effects of trust on performance while others report negligible or no effects [ 124 ]. That being said, trust has an affect on the perception of performance such that when trust is high in a collaboration, the team’s perception of its performance is higher [ 182 ].

Trust is more difficult to establish and maintain in geographically dispersed collaborations [ 170 , 193 , 220 ] for a variety of reasons including the lack of strong relationships common to co-located teams [ 36 , 37 , 38 , 123 ] difficulties having in-depth personal interactions due to the absence of nonverbal cues and difficulties inferring the intentions of others [ 67 ]. Trust is also dependent on frequency of interactions, which may be less in virtual teams [ 273 ]. Swift trust in virtual teams is particularly fragile due to the unexpected disruptions and differences across time, distance, organization, and culture in virtual teams [ 266 ]. Teams that interact virtually are considerably less likely to develop trust [ 216 ]. Furthermore, trust develops in a sequential approach in co-located tams but follows an ad-hoc, unpredictable approach in virtual teams [ 147 ].

This difficulty in establishing trust has profound effects on collaboration, (e.g., (1) corrosion of task coordination and cooperation [ 193 ], (2) decreased eagerness to communicate [ 101 ], (3) inability to systematically cope with unstructured tasks and uncertainty [ 123 ], (4) fewer members willing to take initiative [ 123 ], (5) lack of empathy for teammates [ 132 ], (6) lower amounts of feedback from collaborators [ 123 ]), and increased risk [ 218 ]. Additionally, several studies (e.g., [ 116 , 142 , 188 ]) showed that low trust caused by distance affected workers’ identification of themselves as belonging to a team spanning locations. These issues have detrimental effects on collaborations that can delay or even halt the progress of a project.

Lack of trust is most pronounced during the initial stage of the collaboration and tapers off throughout the course of the project [ 21 ], implying that there are mitigating factors for the effect of distance on trust. Taking social approaches, such as promoting social exchanges early on in the life of a project [ 123 ], or creating opportunities for casual, non-work-related interactions between collaborators [ 193 ], can improve trust. However, these types of informal interactions more commonly occur face-to-face [ 193 ]. Furthermore, [ 186 ] identified face-to-face communication as having an ‘irreplaceable’ role in building and repairing trust.

Face-to-face communication is not always possible in distance collaborations, which is why [ 20 ] investigated challenges associated with trust—particularly delayed trust (slowed rate of progress towards full cooperation) and fragile trust [susceptibility towards negative ‘opportunistic behavior (p. 1)’]—via an evaluation of four communication methods commonly used in distance collaborations: face-to-face, audiovisual (e.g., Skype [ 175 ], Google Hangouts [ 90 ], FaceTime [ 6 ]), audio (telephone), and text-based (email, [ 232 ]) tools. They found that the absence of body language, subtle voice inflections, facial expressions, etc. cause delays in workers’ decisions whether to trust a new collaborator and impede expression of their own trustworthiness. This finding agrees with Olson and Olson’s assertion that the presence of video when communicating helps in situations where workers are not familiar with each other [ 193 ]. The effect of stripping body language, subtle voice inflections, facial expressions, etc. from communication was clearly shown by the performance of people participating in a social dilemma game who relied on distance technology for communication—these collaborations markedly showed more fragile trust than those that communicated face-to-face. Textual communication was especially worse with regards to establishing and maintaining trust, although audiovisual and audio technologies did have some effect on delayed and fragile trust. It is unsurprising then that trust development is enhanced by facilitating an initial face-to-face meeting at the beginning of a team’s relationship [ 163 ]. Furthermore, the effectiveness, reliability, and usefulness of the CMC technology used by the virtual team affects trust [ 42 ]. The personal characteristics of team members (e.g., ability, integrity, competence, fairness, honesty, openness) and the level of autonomy in a team play an important part in establishing trust [ 42 ].

From these works, we see that not only does distance influence trust, but this effect can partially be attributed to the use of communication technology adopted by distance collaborations. This influence may be further affected by the manner in which communication technology is used, since irregular, unpredictable, and inequitable communication between collaborators hampers trust [ 123 ]. Thus, it is important for future research seeking to address trust in collaboration to consider communication methods, particularly since trust in collaboration is still a relevant issue [ 29 , 30 , 217 ].

5.1.3 Informal and face-to-face communication

Prior work has identified team communication as one of the fundamental challenges associated with virtuality [ 5 ]. Communication in virtual teams is a key predictor of various outcomes such as improved performance and increased commitment [ 76 ]. Often in co-located collaborations, informal communication (i.e., ‘coffee talk’ [ 57 ]) accounts for up to 75 minutes of a workday [ 102 ]. These crucial exchanges often occur after meetings or during unplanned encounters in the hallway [ 8 ] and have profound effects on collaboration. In contrast, communications in virtual teams are often more formal than in co-located settings and focus more on work-related issues [ 13 ]. This is as a result of limited opportunities for the informal and unintentional information exchanges that often happen in shared spaces such as the hallway, water cooler, or parking lot [ 13 ]. This in turn diminishes a virtual team’s ability to share knowledge [ 92 ]. Informal contact plays an important role in facilitating trust and critical task awareness [ 2 ]. Spontaneous, informal communication has been shown to foster the feeling of being a part of a cohesive team [ 11 , 102 , 132 ] and assist the provision of corrective feedback [ 8 ]. These types of informal encounters are particularly important for unstable, dynamic groups [ 2 ].

Informal communication is associated with face-to-face encounters [ 73 , 191 ], thus, face-to-face communication plays an important role in collaboration [ 64 ] and has been described as being ‘crucial’ [ 196 ] or ‘indispensable’ [ 11 ], particularly at the beginning of a project. Frequent face-to-face interactions enable collaboration in virtual teams [ 54 ] and is credited with the ability to dramatically boost the strength of work and social ties within the team [ 133 ], which promotes a worker’s sense of belonging to the team and awareness of group activities [ 2 ], as well as boosting mutual trust and understanding, which is critical for preventing conflicts [ 8 ]. In addition, face-to-face communication is associated with higher levels of consensus within groups, higher perceived quality, more communication, and greater efficiency in completing tasks [ 86 ]. For this reason, it is recommended by many authors that members of virtual teams meet face-to-face when possible, particularly during the initial launch [ 136 , 151 , 265 ], when a face-to-face meeting can create a lasting bridge across geographical, temporal, and socio-cultural distance [ 265 ]. (Socio-cultural distance will be discussed in further depth later in Sect.  6.4.2 ) It is unsurprising, then, that traveling for obtaining face-to-face contact is imperative for project success [ 116 ].

Opportunities for informal interactions are greatly reduced by geographic distance between collaborators [ 93 , 132 ]. As a result, remote collaborators are often excluded from spontaneous decisions that are made outside formal meetings [ 8 ]. This exclusion is partly as a result of the increased effort needed to reach out and contact a teammate [ 101 ], and likely partly due to the correlation between distance and diminished face-to-face communication [ 52 , 133 , 141 , 144 ]. Geographic barriers to face-to-face communication include an increase in cost and logistics [ 2 ] and the burdens of travel in terms of money and time [ 11 ].

It is no surprise, then, that virtual teams show a marked increase in online activity [ 191 , 213 ] and have a higher reliance on CMC technology [ 215 ]. computer-mediated communication technology refers to the use of computers for communication between individuals []. This technology includes audiovisual, audio, and text-based tools. Use of this technology comes with significant challenges. Synchronous technology (i.e., audio and audiovisual tools) requires that all parties be available at a particular time. Some research has shown that it may be difficult to ascertain a remote collaborator’s availability for a synchronous meeting [ 101 ] and electronic-communication dependence constrains informal, spontaneous interaction [ 61 ], while others argue that CMC is dynamic and can be used on an ad-hoc and as-needed basis with no need for scheduling, presenting fewer logistical challenges [ 234 ]. However, it is important to note that, like in the case of the telephone, initiating spontaneous communication could be perceived as intrusive [ 144 ]. In addition, audio technology ‘distorts’ verbal cues and removes visual cues [ 20 ]. Audiovisual technology is also known to mask both verbal and visual cues in addition to constraining the visual field [ 20 ]. CMC often lacks support for non-direct and nonverbal interactions (e.g., body language, facial expressions) which greatly hinders communication in geographically dispersed virtual teams [ 67 ] by making interactions more difficult [ 92 ]. Thus, the choice of CMC technology has a heavy influence on communication because each method offers a different capacity to convey verbal and nonverbal cues [ 178 ]. It is therefore recommended to use several types of CMC technologies either concurrently (e.g., face-to-face communication accompanied by documents; telephone conferencing with synchronous electronic conferencing) or consecutively (e.g., conveying information via e-mail first, followed by con verging over the phone) [ 60 ].

Virtual teams that rely on CMC in lieu of face-to-face communication are more likely to experience less positive affect and have a diminished affective commitment to their teams [ 126 ]. Furthermore, compared to face-to-face feedback, computer-mediated feedback reduces perceptions of fairness [ 3 ]. This lack of face-to-face contact results in virtual teams having a lower sense of cohesion and personal rapport between team members [ 263 ]. Members of virtual teams may also divide their attention between various tasks while simultaneously participating in teamwork interactions due to the asynchronous nature of communication media, resulting in a lack of investment in the tasks [ 163 ]. As a result, communication timeliness has a higher influence on performance in virtual teams [ 163 ]. Furthermore, virtual teams that rely on CMC technology (e.g., instant messaging) to supplement communication in the absence of face-to-face interactions may have difficulties in their decision-making processes [ 173 ].

However, overall, communication technologies (including text-based tools) take more time and effort to effectively communicate information and are missing important social information and nonverbal cues that help establish ties between collaborators [ 64 ]. This has important implications for situations where a high volume of communication is necessary. Due to the extra effort required to communicate through computer-mediated modalities (e.g., email), virtual teams must put in extra effort to manage high volumes of messages, which can hinder performance [ 163 ]. Furthermore, when teams use email for communication, it becomes difficult to determine whether the information contained within the email was understood in the absence of vocal and nonverbal cues [ 163 ]. To combat this, Marlow et al. [ 163 ] suggest using closed-loop communication to prevent misunderstandings by providing opportunities for clarification that would otherwise not accompany virtual communication. They argue that the use of closed-loop communication will enhance performance in virtual teams [ 163 ].

Since remote collaborations must rely on technology in lieu of face-to-face communication, the level of technical competence of the team members can pose an additional challenge [ 193 ]. Teams that are unable to adopt and integrate basic technology into their everyday workflow are unlikely to use more complicated and sophisticated collaboration technology (e.g., multi-pane videoconferencing) [ 191 ] that may better support visual and verbal cues, enriching distance communication. Furthermore, the level of technical infrastructure can also create collaboration challenges [ 193 ]. Technology for remote work fails without adequate technical support or resources. Reliability is also an issue with communication technology—new technology must be stable enough to ‘compete with the well-established reliability of the telephone’ [ 15 ].

There are some advantages to using commuter-mediated communication technology in virtual teams. For example, asynchronous technology (e.g., text-based tools) provide provide the ability to take one’s time when asking a question or crafting a response [ 144 , 261 ], which leads to efficient, focused conversations [ 77 , 144 ] that can be quicker than other forms of communication. CMC is also shown to increase participation among team members [ 212 ], facilitate unique ideas [ 86 , 212 ], and reduce the number of dominant members [ 212 ]. In a similar vein, Fjermestad [ 79 ] found that groups that relied on CMC experienced higher decision quality, depth of analysis, equality of participation, and satisfaction than groups that primarily met face to face. Finally, virtual teams that do not meet face to face may be better at adapting their conceptualization of a task in response to a team member completing a task in a novel manner [ 163 ]

Additional factors, such as experience with a task, interdependence, and the temporal stage of team development can impact team performance when relying on CMC technology. For example, when teams have experience with the task at hand, with each other, and with their communication method, there is less of a need for synchronous CMC technology (e.g., video conferencing) [ 60 ]. In contrast, when teams do not have this extensive experience, there is a greater need for synchronous CMC technology [ 60 ]. Organizational structure, levels of interdependence, and media richness (which ranges from face-to-face communication to simple documents) also influence the effectiveness of communication [ 140 ]. These factors vary depending on the communication method’s capacity for immediate feedback, ability to facilitate nonverbal cues, and level of personalization [ 140 ]. In addition to this, Maruping and Agarwal [ 165 ] found that matching the functionalities of the CMC technology to specific tasks will result in higher levels of effectiveness in virtual teams. Furthermore, stage at which a virtual team is at in their development will also affect communication [ 165 ]. Teams in their early stages of development should use CMC technologies that facilitate expression in order to mitigate relationship conflict [ 165 ]. Video-conferencing technologies are particularly suited for this situation being both synchronous and media rich [ 165 ].

From the identification of these challenges, we can clearly see that existing tools and infrastructures have limitations that are preventing communication technology from fully supporting informal interactions. Thus, we are left with a need for other methods that support informal communication in geographically dispersed collaborations.

5.1.4 Intra-team conflict

In Jehn et al.’s exploration of everyday conflict through qualitative investigation of six organizational work teams, intra-team conflict is categorized as being either affective (i.e., interpersonal), task-based, or process-based (i.e., relating to responsibilities and delegation of workers for tasks) [ 125 ]. All three types of conflict have been investigated within the context of geographically distributed versus co-located teams, with mixed results. Several researchers have concluded that geographically distributed teams experience higher levels of conflict [ 8 , 46 , 103 , 108 , 188 , 261 ]. In particular, geographically distributed teams are more susceptible to interpersonal [ 108 ] and task-based conflict [ 108 , 179 ]. There is some evidence that conflict has a more ‘extreme’ [ 107 , 159 ] or ‘detrimental’ [ 179 ] effect on distributed teams as opposed to co-located ones. This effect can likely be attributed to the evidence that conflict in distributed teams is known to escalate and often remains unidentified and unaddressed for long periods of time [ 8 ]. As a result of reliance on computer-mediated communication, virtual teams featuring high geographical dispersion have higher perceptions of unfairness, which also leads to internal conflict [ 244 ].

One pervasive issue is the development of geographically based subgroups within a collaboration that provoke us-versus-them attitudes [ 8 , 46 ]. Armstrong and Cole observed that the word ‘we’ was often used to refer to co-located workers, regardless of which group the workers were assigned [ 8 ]. In another case, a team of international collaborators spread across four sites ‘fought among themselves as if they were enemies’. Interviews exposed that the team was actually comprised of four groups under one manager and did not act or feel like one cohesive team [ 8 ]. These conflicts are similar to those associated with communicating at a distance. Conflicts frequently occur as a consequence of assumptions and incorrectly interpreted communications [ 103 ]. Furthermore, missing information and miscommunications between geographically distant sites result in teammates making harsh attributions about their collaborators at other locations [ 46 ]. These types of intra-group conflicts can have important ramifications for distant collaborations. Us-versus-them attitudes often lead to limited information flow, which in turn leads to reduced cohesion and faulty attributions [ 46 ]. Moreover, intra-team conflict causes problems that result in delays in work progress [ 8 ] and resolution of work issues [ 103 ].

Researchers have identified several things that can mitigate conflict in virtual teams. Both shared context [ 108 ] and a shared sense of team identity have a moderating effect on conflict [ 108 , 179 ], particularly task and affective conflict [ 108 , 179 ]. Familiarity, in addition, has been shown to reduce conflict [ 107 ]. Spontaneous communication—which, as previously discussed, is primarily achieved face-to-face—has been demonstrated to mitigate conflict in virtual teams, particularly due to its role in facilitating the identification and handling of conflict [ 108 ]. There are also more instances of task conflict in teams that rely heavily on communication technology [ 179 ]. Specific types of conflict can be managed through different forms of computer-mediated communication technology. Task related conflict, for example, is best managed through synchronous communication technologies such as video-conferencing [ 165 ]. Conflict related to processes can be effectively handled using asynchronous communication technologies that also document the team’s agreements regarding tasks and responsibilities [ 165 ]. In this case, immediate feedback is not as necessary [ 165 ].

Although the above work has come to an agreement as to whether geographic distance has a negative effect on conflict, contradictions do exist in the literature. In particular, Mortensen and Hinds’ [ 179 ] examination of 24 product development teams found no significant difference in affective and task-based conflict between co-located and distributed teams, which is in direct conflict with their later work [ 108 ]. This discrepancy is particularly interesting given that the participants in both studies did research and product development, and are therefore comparable. Thus, it is uncertain as to which conclusion is accurate, presenting an open question.

5.2 Temporal distance

Temporal distance is distinctly different than geographical distance and should be treated as a separate dimension [ 49 ]. While geographical distance measures the amount of work needed for one collaborator to visit another at that collaborator’s place of work, temporal distance is considered to be a directional measurement of the temporal displacement experienced by two collaborators who want to interact with each other [ 2 ]. Temporal distance can be caused by both time shifts in work patterns and differences in time zones [ 219 ]. In fact, time zone differences and time shifts in work patterns can be manipulated to either decrease or increase temporal distance [ 2 ]. It can be argued that temporal distance is more influential than geographic distance [ 75 , 213 , 243 , 250 ] due to the challenges it poses on coordination [ 49 , 74 , 75 , 141 , 183 , 213 , 243 ].

One key disadvantage to high temporal distance is the reduced number of overlapping work hours between collaboration sites [ 11 , 33 , 132 ]. Although in an ideal situation, having team members dispersed across time zones can allow continual progress on a project as each team member works within their respective workdays [ 256 ], this isn’t always the case. In fact, temporal distance can lead to incompatible schedules that result in project delays and can only be overcome with careful planning [ 230 ]. Fewer overlapping work hours results in communication breakdowns, such as an increased need for rework and clarifications, and difficulties adjusting to new problems [ 73 , 74 ]. Additionally, reduced overlap in work hours results in coordination delays [ 49 ]. For example, a distant teammate may not be available when their expertise is needed [ 2 ]. In some cases, this unavailability causes the collaborator in need of help to make assumptions based on local culture and preferences in order to reach an immediate resolution of issues—which can cause rework when these assumptions are incorrect [ 250 ]. The issue of the lack of overlapping work hours also causes problems with synchronization; synchronous communication is often significantly limited in temporally dispersed collaborations, which can delay vital feedback [ 2 ] and increase response time [ 219 ]. In fact, scheduling global meetings can be virtually impossible for this reason [ 250 ]. Furthermore, as with geographic distance, temporal distance decreases the number of opportunities for informal communication [ 93 , 132 ] since the window in which all collaborators are available is small.

Communication can be disrupted by temporal distance in other ways. Bjørn and Ngwenyama found that in some virtual teams, communication would become limited to temporally co-located teammates because it was easier, bypassing teammates at other sites who should have been included [ 14 ]. This invisible communication would result in collaborators feeling left out of key decisions, which had toxic effects on the project. This effect is especially unfortunate given that temporal distance makes repairing the consequences of misunderstandings and reworking portions of the project more costly [ 73 ].

In addition to these issues, temporally dispersed collaborations are often plagued by delays, while co-located collaborations are considered more efficient [ 19 ]. Coordination delay increases with temporal distance—delay between collaborators located in the same city was smaller than that for collaborators in different cities, which was smaller than the delay found in collaborators located in different countries [ 49 ]. Delays in responses from collaborators can be especially frustrating and problematic [ 116 ] and can lengthen the amount of time required to resolve issues [ 19 ], sometimes dragging problems out across multiple days [ 120 , 132 ]. When work is organized such that a team member’s contribution is dependent upon a task completed by a team member in an earlier time zone, a failure to complete the earlier task can result in the loss of an entire workday [ 250 ]. Thus, timely completion of tasks in temporally dispersed collaborations is crucial [ 250 ]. Coordination delays are also shown to cause additional problems, particularly decreased performance in terms of meeting key requirements, staying within the budget, and completing work on time [ 49 ].

There are several social approaches to mitigating these issues. For example, collaborators can cultivate flexible work schedules [ 116 ], often by modifying a ‘typical’ workday by working either extremely early in the morning or very late at night so that there are overlapping work hours [ 250 ]. In contrast, Holmstrom et al. found that both Hewlett Packard (HP) and Fidelity employed a ‘follow-the-sun’ concept where work is handed off at the end of the day in one time-zone to workers beginning their day in another [ 116 ]. Follow-the-sun methodologies, if used effectively, can result in efficient, 24/7 productivity since work can be completed by one team member during another’s off hours [ 2 , 93 , 103 ]. However, this technique requires additional oversight time to facilitate the transfer of work from one team to the other, including time to discuss arising issues [ 250 ]. A competing technique is to limit the number of time zones in which sites are located [ 116 ]. Additionally, some coordination issues can be mitigated by careful division of work which takes into account being separated by several time zones [ 49 ].

Technology also plays a key role in mitigating the effects of temporal distance. Asynchronous communication tools (e.g., email, fax [ 19 , 57 ]) allow collaborators to coordinate shared efforts across time and distance with the additional benefits of leaving a written communication history [ 31 ] that supports accountability and traceability [ 2 ]. However, using asynchronous tools is known to increase the amount of time that a collaborator has to wait for a response [ 2 ] and make temporal boundaries more difficult to overcome than spatial boundaries in instances where sites do not have overlap in their workdays [ 49 ]. Furthermore, the process of writing ideas in emails increases the risk of misunderstandings between collaborators [ 57 ] over talking in person or via the telephone. Finally, developers starting their workday may become overwhelmed by the number of asynchronous messages left during the previous night [ 19 ]. Given these drawbacks to current technology and the unlikelihood that global collaboration is going to stop, it is worthwhile to ask how can we better support communication in temporally distant work.

There is also some question as to whether coordination costs are higher in teams that are temporally distributed. Both Ågerfalk et al. [ 2 ] and Battin et al. [ 11 ] assert that temporal distance greatly increases the cost and effort of coordination due to the added difficulties of dividing work across multiple time zones. Espinosa and Carmel [ 73 ], however, state that temporal distance reduces coordination costs when team members are not working concurrently because no direct coordination takes place when the two teammates are not working at the same time [ 2 ]. Clearly, this discrepancy needs to be resolved.

5.3 Perceived distance

As previously discussed in Sects. 5.1 and 5.2 , distance is commonly conceptualized in terms of geography or time zones [ 4 ] (i.e., spatio-temporal distance). In contrast, perceived (a.k.a. subjective) distance is characterized by a person’s impression of how near or how far another person is [ 270 ]. These perceptions of proximity have both an affective and a cognitive component [ 189 ]. In this case, the cognitive component refers to a mental judgement of how near or distance a virtual teammate seems while the affective component is concerned with the idea that a person’s sense of perceived proximity is neither purely conscious or rational but is instead dependent on emotions [ 189 ]. Perceived distance is a distinctly different idea than spatio-temporal distance and one is not necessarily related to the other [ 215 ]. Rather, perceived distance is the “symbolic meaning” of proximity rather than physical proximity and is suggested to have a greater effect on relationship outcomes [ 189 ]. This symbolic meaning is defined by the teams sense of shared identity and their use of communication media, which is primarily synchronous [ 189 ]. In fact, as people interact strongly and frequently with other team members, they can create a sense of closeness independent of physical proximity [ 214 ]. For example, free and open source software developers often perceive high levels of proximity due to their strong and intense communication and “hacker” identities [ 214 ]. The concept of perceived distance is why collaborators may be geographically distant and yet feel as though they are proximally near [ 162 ]. Perceived proximity can have a profound influence on team interaction [ 34 , 82 , 189 ] For example, perceptions of proximity are known to influence decision making in virtual teams [ 198 ].

In 2014, Siebdrat et al. surveyed 678 product developers and team leaders in the software industry to investigate perceived distance and challenge the notion that geographic and temporal distance directly translates to perceived distance. They found that perceived distance was more strongly affected by a team’s national heterogeneity than by their spatio-temporal distance. Furthermore, Siebdrat et al. found that perceived distance had a significant effect on collaboration while spatio-temporal distance had no impact. As a result, they concluded that perceived distance is more indicative of collaboration challenges than spatio-temporal distance.

Findings from other work implies that distance can affect collaborators that are all in the same country at a single site [ 4 ], with low national heterogeneity and low spatio-temporal distance. It is uncertain whether this situation would still have high perceived distance given the limited work available. Therefore, there is a clear need for a better understanding of the relationship between perceived distance, spatio-temporal distance, and collaboration.

6 Contributing factors

In addition to the challenges associated with the three main types of distance discussed previously in this paper (i.e., geographic, temporal, and perceived distance), several contributing factors intersect with distance to cause additional challenges for virtual teams. To answer Question 1b (What other factors contribute to the factors and challenges that impact distance collaboration?), this paper will discuss these key factors, namely the nature of work, the need for explicit management, configuration, and diversity of workers in a collaboration.

6.1 Nature of work

Work can be categorized as either loosely or tightly coupled [ 191 ]. Tightly coupled work relies heavily on the skills of groups of workers with exceedingly interdependent components; this type of work necessitates frequent, rich communication and is usually non-routine. Loosely coupled work, in contrast, is typically either routine or has fewer dependencies than tightly coupled work. Interdependence between components, and thus tightly coupled work, is at the heart of collaboration [ 225 ]. In addition, complex tasks lead to higher trust and collaboration than simple tasks and task complexity is a critical factor that molds the interactions and relationships between team members [ 42 ]. Furthermore, interdependence is not merely an issue of sharing resources, but instead ‘being mutually dependent in work means that A relies positively on the quality and timeliness of B s’ work and vice versa and should primarily be conceived of as a positive, though by no means necessarily harmonious interdependence’ [ 225 ]. Marlow et al. [ 163 ] found that as interdependence increases, communication becomes increasingly critical. They therefore suggest that communication becomes increasingly important to promoting high levels of performance. In 1988, Strauss described the additional work necessary for collaborators to negotiate, organize, and align their cooperative (yet individual) activities that occur as a result of interdependence. In doing so, Strauss discusses the concept of articulation work—by his definition, work concerned with assembling tasks and adjusting larger groups of tasks (e.g., sub-projects and lines of work) as a part of managing workflow. Articulation work is further described as the additional work needed to handle the interdependencies in work between multiple collaborators [ 72 ].

Virtual teams face greater challenges when managing these dependencies as a result of distance, both spatial and temporal, and culture [ 72 ]. Because interdependent (i.e., tightly coupled) work requires a high amount of interaction and negotiation, it is very difficult to do at a distance [ 191 ]. In contrast, loosely coupled work does not require as much communication as tightly coupled work, and so is easier to complete in geographically distant collaborations. Thus, tightly coupled work in virtual teams leads to less successful projects [ 193 ]. This observation is important since most projects have both varieties of work [ 191 ].

To combat the challenges associated with relying on tightly coupled work, many organizations take a social approach that arranges for co-located team members to work on tightly coupled aspects of the project while distance workers tackle loosely coupled parts [ 64 , 193 ], facilitated by deconstructing tasks into smaller pieces [ 93 ]. For tightly coupled work, some organizations choose to use extreme [ 161 ] or radical [ 246 ] collaboration setups where teams work in an enclosed environment in order to maximize communication and facilitate the flow of information. In contrast, for loosely coupled work, some organizations choose to minimize interaction [ 104 ]. Creating rules and norms for communication between team members early in the team’s life cycle can also increase effective communication and therefore improve performance during complex tasks [ 262 ]. This is essential for managing highly complex tasks and avoiding misunderstandings that can arise as a result of high task complexity combined with high virtuality [ 163 ].

However, the idea that tightly coupled work challenges collaboration is contested by Bjørn et al. [ 15 ]. This case study is centered on a large research project investigating global software development with several geographically dispersed partners. This study also provides evidence that tightly coupled work resulted in stronger collaborations. They observed that tightly coupled work required collaborators to frequently interact to do their work and, as a result, forced these collaborators to know more about each other, help each other, and cultivate strong engagement despite being at geographically distant sites. In contrast, loosely coupled work did not require the same level of engagement, resulting in collaborators feeling more detached from the project. Thus, Bjørn et al. proposed that tightly coupled work in geographically distributed teams involves processes that help collaboration [ 15 ].

Complex, tightly coupled tasks may be more difficult to the reliance of virtual teams on virtual tools and tendency to disband after a task has been completed [ 12 ]. Furthermore, the combination of high task complexity and high levels of virtuality lends itself to misunderstandings and mistakes [ 163 ]. As a result, effective communication is more critical for high performance in virtual teams for these tasks [ 163 ]. Despite this, Marlow et al. suggest that virtual teams can successfully complete these tasks if team members cultivate shared cognition. Given the characteristics of CMC technologies like video conferencing, which preserve much of the nuances present in face-to-face communication, we posit that shared cognition can be developed through the frequent, consistent use of this medium for communication.

Given the contrast between the work suggesting that tightly coupled work hinders distance collaboration [ 72 , 191 , 193 ] and work by Bjørn et al. [ 15 ] that suggests the opposite, there is clearly room for further research on the subject. This is especially true since Bjørn et al. focused only on global software development, and thus their findings might not generalize to other types of collaboration.

6.2 Explicit management and leadership

One of the largest challenges faced by virtual teams is the management of team effort [ 207 ]. Explicit management is needed for distributed, collaborative work, particularly by leaders trained in project management, in order to ensure the success of a project [ 150 , 193 ]. Collaborative projects are considered difficult to manage, especially as the number of workers associated with the project increases. Leadership is challenging in geographically dispersed teams because effective leadership is highly dependent on quality interactions that are more difficult across distance [ 157 ]. For example, Hoch and Kozlowski [ 111 ] found that hierarchical leadership is less effective in geographically dispersed teams than in co-located teams. It is also more challenging to ensure that the team’s work is given priority by the team members in geographically dispersed teams [ 131 ]. Furthermore, distributed projects face even more obstacles, such as increased coordination problems [ 188 ] including identifying and overcoming cultural differences, ensuring that all team members are heard [ 193 ], and regulating the inter-dependencies between resources, task components, and personnel [ 158 ].

Virtual teams face challenges related to leadership, such as nourishing an environment that fosters creativity [ 96 ] and emergent leadership [ 35 ]. Effective leadership benefits geographically dispersed virtual teams in a multitude of ways, including helping virtual teams overcome many of the challenges caused by distance, including facilitating satisfaction and motivation [ 88 , 169 ]. Virtual leadership can help collaboration within the team through providing training, guidance, resources, coaching, and facilitating relationship building [ 150 ]. Furthermore, leadership in virtual teams can facilitate knowledge sharing and the building of shared mental models [ 150 ]. Mental models are defined by Johnson-Laird [ 126 ] as internal representations of knowledge that match the situation they represent and consist of both abstract concepts and perceptible objects and images. These mental models may reflect detailed information about how the task is to be performed (i.e., task-related team mental models) or information about team member’s roles, tendencies, expertise, and patterns of interaction (i.e., teamwork-related mental models) [ 226 ]. These benefits, in turn enhance virtual team effectiveness [ 150 ]. Task complexity can be a mitigating factor in the effectiveness of leadership. Leadership benefits the team more in an environment where tasks are highly interdependent and/or highly complex [ 150 ]. In addition to this, team members’ perceptions of their leaders’ use of communication tools and techniques can impact their perceptions of overall team performance [ 182 ]). In particular, positive perceptions of leadership communication results in positive perceptions of performance [ 182 ].

Leadership can have a strong influence on interpersonal team dynamics and trust as well. Prior work indicates that leaders play an important role in enhancing team performance by demonstrating empathy and understanding [ 131 ], monitoring and reducing tensions [ 260 ], and clearly articulating role and relationship expectations for team members [ 131 ]. Leaders in virtual teams have the capacity to prevent and resolve team relationship and task conflicts [ 150 ]. Furthermore, effective leadership can have a positive influence on affection, cognition, and motivation [ 150 ]. It is particularly important for leaders to bridge co-located and remote team members in order to promote team effectiveness [ 150 ]. Leaders can build trust within virtual teams by engaging in behaviors such as early face-to-face meetings, using rich communication channels, and facilitating synchronous information exchange [ 150 ]. High levels of consistent communication between leaders and team members is positively related to trust and engagement within virtual teams [ 80 ].

Individual leadership styles have their own impact on virtual team productivity. Prior work has focused on four key types of leadership: transformational, empowering, emergent, and shared. Transformational leadership is characterized by idealized influence, inspirational motivation, individual consideration, and intellectual stimulation [ 65 ]. This type of leadership enables followers to reach their potential and maximize performance [ 65 ]. However, transformational leadership, while effective in co-located or slightly dispersed teams, is less effective in improving the performance of highly geographically dispersed teams [ 69 ]. This may be due to the difficulties associated with facilitating communication across distance, which can cause the leader’s influence to have counterproductive effects [ 69 ]. In this case, the leader is likely to be “too far removed” to authentically want to make a difference [ 69 ]. In fact, a transformational leader’s influence on team communication decreases as the team becomes more and more dispersed [ 69 ].

Empowering leadership combines sharing power with individual team members while also providing a facilitative and supportive environment [ 236 ]. High empowering leadership has the effect of positively influencing team members’ situational judgement on their virtual collaboration behaviors and, ultimately, individual performance [ 105 ]. Moreover, empowering leadership has a positive effect on team performance at high levels of team geographic dispersion [ 105 ]. However, it is important to note that teams may miss out on the benefits provided by empowering leadership if they lack situational judgement [ 105 ]

Emergent leaders are people who exert significant influence over other members of a team, even though they may not be vested with formal authority [ 227 ]. Emergent leadership has a positive relationship with virtual team performance [ 110 ]. In particular, emergent leadership has positive relationships with team agreeableness, openness to experience at the individual team member level, and emotional stability [ 110 ]. In addition, emergent leadership has a positive relationship to individual conscientiousness, which is associated with being careful, responsible, and organized [ 110 ]. These all have positive influences on virtual team performance [ 110 ].

Shared leadership is a collective leadership processing featuring multiple team members participating in team leadership functions [ 110 ]. This form of leadership can be described as a “mutual influence process” where members of a team lead each other towards the accomplishment of goals [ 109 ]. Shared leadership has a positive influence on the performance of virtual teams [ 110 , 150 ]. The structural support provided by shared leadership can supplement traditional leadership; in this situation, shared leaders assume the responsibility of building trust and relationships among team members [ 150 ]. Shared leadership provides many benefits to virtual teams such as emotional stability, agreeableness, mediating effects on the relationship between personality composition and team performance [ 110 ]. Shared and emergent leadership styles share some effects on virtual teams. Specifically, these types of leadership will affect the relationships between team conscientiousness, emotional stability, and team openness such that they will be stronger in teams with higher levels of virtuality than in teams with lower levels of virtuality [ 110 ]. However, shared leadership is facilitated by the socially-related exchange of information that creates commitment, trust, and cohesion among team members [ 110 ]. In co-located teams, this exchange of knowledge is enabled through social interactions like informal conversations, socializing outside of work, and through meetings [ 110 ]. However, this type of informal and face-to-face communication is less common and feasible in virtual teams for reasons that will be discussed later. As a result, it is necessary for organizations to make efforts to facilitate shared leadership through training [ 110 ].

In addition to leadership style, the level of authority differentiation and skill level of the team members have an affect on team-level outcomes. Among teams with less skilled members, centralized authority (i.e., high authority differentiation) will have a positive influence on efficiency and performance in virtual teams [ 223 ]. In contrast, centralized authority has a negative influence on team innovation, learning, adaption, and performance as well as member satisfaction and identification among teams with highly skilled members [ 223 ]. Decentralized authority (i.e., low authority differentiation) when combined with careful intervention of a formal or informal leader can benefit coordination, learning, and adaptation in virtual teams with high skill differentiation and high temporal stability [ 150 ].

Other studies showed that virtual teams face challenges that could be mitigated with explicit management [ 83 , 188 , 243 , 261 ]. O’Leary and Mortensen investigated the effects of configuration (i.e., the distribution of team members across multiple sites) on team dynamics at the individual, subgroup, and team level [ 188 ]. They found that geographically defined subgroups led to significantly negative outcomes with regards to coordination problems (e.g., difficulties with coordination-related decisions about schedules, deadlines, and task assignments). The effects of configuration on distance work will be discussed further in this section. Similarly, problems of coordination (e.g., ‘reaching decisions’ and ‘division of labor”) were significantly increased by distance [ 261 ]. These results are complemented by findings that distance hampers the coordination of virtual teams via synchronous meetings [ 243 ]. Similarly, coordination in distance collaborations is hindered by difficulties in scheduling synchronous meetings due to limited windows of time where all parties are able to be present [ 83 ]. These findings complement those of Sect.  5.2 discussing the effect of temporal distance on collaboration.

Prior work has suggested various strategies for effective leadership and explicit management. For example, Hill and Bartol [ 105 ] suggest team training that focuses on strategies for overcoming challenges encountered in dispersed teamwork. Another, related, strategy is to focus more attention on setting norms for behavior that may aid appropriate situational judgment among team members when launching geographically dispersed teams [ 105 ]. A different approach is to consider personality dimensions such as agreeableness, conscientiousness, openness, emotion stability, and moderate extroversion, which all have positive influences on team performance, when selecting virtual team members [ 110 ].

However, some types of collaborations, particularly research collaborations consisting mainly of scientists, avoid the application of explicit management in their projects [ 193 ]. There is an opportunity for research to investigate how to support explicit management in distance collaborations that typically reject this type of administration.

6.3 Configuration

Like O’Leary et al. [ 188 ], in this paper, configuration is subdivided into three dimensions: site, imbalance, and isolation. Site dispersion is best characterized as the degree to which collaborators are at distinct geographic locations [ 187 ]. There is an inverse relationship between the number of sites and project success [ 50 , 51 , 133 ]. High site dispersion is associated with higher amounts of faultlines (i.e., theoretical divisions within a group that create subgroups) which damage team collaboration [ 47 , 210 ]. Specifically, faultlines escalate polarization, subgrouping, and the effect of causing collaborators in other locations to feel more distant [ 47 ]. Having a large number of sites, in particular, increases the odds that differences in demographics will create these divisions [ 47 ]. Additionally, greater numbers of sites predict fewer coordination activities and decreased outcomes [ 133 ]. Knowledge sharing decreases [ 40 , 83 ] and the cost of managing team goals increases [ 97 ] as the number of sites increases.

Imbalance refers to the proportion of collaborators dispersed across a set of sites and can have negative effects on collaboration, such as conflicts between large and small sites [ 8 ]. For example, imbalanced teams often have unequal amounts of contribution towards shared team tasks [ 188 ]. Furthermore, levels of conflict and trust differ between imbalanced and balanced teams [ 188 , 210 ]. In particular, larger subgroups in imbalanced teams feel stronger effects from faultlines on conflict and trust [ 210 ]. However, it is unclear what the ramifications are of these differences in trust and conflict [ 188 , 210 ], presenting an opportunity for research.

Imbalanced teams consisting of one isolated collaborator working with a co-located team function differently than highly dispersed, balanced teams [ 188 ]. For instance, communication in these imbalanced teams is different because the co-located team members communicate both face-to-face and electronically with each other, but, in the absence of travel, only communicate electronically with the isolated team member [ 231 ]. This disparity in communication methods impedes informal interaction and spontaneous communication [ 45 ]. This also has a unique effect on communication where the co-located team feels compelled to communicate with those isolated collaborators more frequently to make up for this difference [ 188 ]. Also, isolated members tend to contribute more frequently than their co-located counterparts because they feel as though they need to ‘speak up’ and be ‘heard’ over the co-located team [ 141 , 188 ].

Furthermore, isolation negatively affects a worker’s awareness of collaborator’s activities [ 187 ]. Isolated workers are also more likely to feel the effects of a lack of motivational sense of the presence of others [ 193 ]. These isolated workers identify less with the team and feel less like they are part of the group, leading to a feeling of distance from the rest of the team [ 45 ], which translates to feeling differently about group processes and outcomes [ 27 ]. Furthermore, isolation and feelings of alienation can have a negative effect on relationships among workers in geographically dispersed virtual teams, increasing the likelihood of feeling discomfort and reducing the likelihood of trusting team members that they do not know well [ 67 ].

Configurationally imbalanced teams (i.e., teams that have an uneven distribution of members across sites) tend to have lower identification with teammates and higher levels of conflict [ 188 ]. Conflict can be reduced by a shared sense of team identity [ 108 , 179 ], meaning that fostering this sense of identification with the team can mitigate both problems. Since team identification can be built via face-to-face communication [ 54 ]; we posit that in the absence of face-to-face communication, imbalanced teams should make use of CMC technologies that facilitate nuanced expression, such as video conferencing tools.

6.4 Group composition

The diversity of a team encompasses several factors that correlate with a set of challenges that greatly affect virtual teams. This section will focus on the issues of common ground, socio-cultural distance, and work culture. In the process, this section will discuss the remaining challenges identified by Olson and Olson [ 191 , 193 ], (continued from Sect.  5 ): common ground, the competitive/cooperative culture, and alignment of incentives and goals.

6.4.1 Common ground

Distance collaboration becomes easier if team members have common ground (i.e., have worked together before [ 54 ], have shared past experiences [ 54 ], vocabulary [ 191 ], or mental models [ 168 ] etc.) since it allows them to communicate via technology without requiring frequent clarification [ 193 ]. This challenge is also referred to as the ‘mutual knowledge problem’ [ 46 ]. The concept of mutual knowledge between teammates is based on the idea of ‘grounding’ in communication [ 43 ], which is done by both communicating and confirming understanding using words or body language [ 43 ]. Schmidtke and Cummings [ 226 ] found that as virtualness increases in a team, mental models become more complex, which negatively affects teamwork. They also found that as virtualness increases, similarity and accuracy of mental models decreases [ 226 ]. Accuracy and similarity play vital roles in reducing the negative effect of complexity on teamwork behaviors [ 226 ]. Fortunately, specialized training can increase mental model accuracy [ 226 ].

As virtual teams rely more on computer mediated communication, temporal stability (i.e. “the degree to which team members have a history of working together in the past and an expectation of working together in the future” [ 115 ]) more strongly influences teamwork [ 223 ]. High temporal stability is associated with positive team outcomes related to related to adaptation, learning, innovation, and performance, as well as satisfaction and identification with the team [ 223 ]. In addition to this, the extent to which virtual team members share common goals is critical in determining the success of the team [ 42 , 230 ]. For this reason, team leaders should ensure that team members commit to the task and common goals [ 10 ].

Research [ 168 ] has shown that it is more difficult for virtual teams that are geographically dispersed to develop a shared mental model. In particular, the process of grounding is made more difficult when there is a higher risk of misinterpretation, such as in the presence of multiple cultural practices and languages [ 191 ].The significant amount of time required to establish common conceptual frameworks and personal relationships can pose a significant constraint on collaboration in virtual teams [ 54 ].

The consequences of lack of common ground are primarily difficulty building trust [ 123 , 202 , 273 ] and difficulties associated with communication. Lack of common ground can limit the ability to communicate about and retain contextual information about teammates located at other sites, including their teammates situation and constraints, especially as the number of sites increases, in turn hindering their collaborative interactions and performance [ 46 , 230 ]. This contextual information includes, but is not limited to, local holidays and customs, site-specific processes and standards, competing responsibilities, and pressure from supervisors and teammates [ 46 ]. Common ground is also necessary to understand which messages or parts of messages are the most salient, which is particularly problematic because there may be restricted feedback [ 46 ]. The lack of common ground can also create problems interpreting the meaning of silence, which makes it difficult to know when a decision has been made [ 46 ]. Furthermore, lack of common ground can result in an uneven distribution of information and differences in speed of access to that information, which causes teammates at different sites to have different information and creates misunderstandings that are nontrivial to rectify [ 46 ].

Thus, the establishment of common ground is of utmost importance to virtual teams.

6.4.2 Socio-cultural distance

Socio-cultural distance has been defined as a measurement of a team member’s perception of their teammate’s values and usual practices [ 2 ]. This concept encompasses national culture and language, politics, and the motivations and work values of an individual [ 2 ]. It is known that geographically distributed collaborations are more socio-culturally diverse than co-located ones [ 179 ] because distance typically increases demographic heterogeneity (especially racial or ethnic heterogeneity) [ 107 ]. Members of a virtual team with different cultural backgrounds are likely to have different behaviors within the teams, including how they interact with their teammates [ 123 ]. For this and other reasons, virtual team’s cultural composition is the key predictor of the team’s performance [ 242 ].

Cultural differences go beyond national differences. There is a tendency for researchers studying cross-cultural organizational behavior to focus on national issues or use nation as a substitute for cultural values [ 245 ]. However, nation is not the only meaningful source of culture [ 84 , 149 ]. In addition to this, there may be multiple subcultures within a nation and the national culture may not be completely shared [ 135 ]. In fact, variation of cultural values within a country may be higher than variation between countries [ 114 ]. Therefore, a virtual team with high national diversity may not necessarily be culturally diverse [ 86 ].

Prior research has identified three levels of diversity: surface-level, deep-level, and functional-level [ 99 , 177 ]. Surface-level diversity is primarily observable differences such as race, age, and sex, while deep-level diversity is comprised of more subtle differences in personal characteristics such as attitudes, beliefs, and values, which are communicated through interaction between team members and information gathering [ 177 ]. Functional-level diversity, in contrast, refers to the degree to which team members have vary in knowledge, information, expertise, and skills [ 10 ].

The individualism-collectivism dichotomy is a ‘major dimension of cultural variability’ [ 112 ] that contributes to high socio-cultural distance. Socio-cultural distance is associated with higher levels of conflict as well as lower levels of satisfaction and cohesion [ 238 ] and has a profound impact on team performance [ 70 ]. Hardin et al. [ 98 ] found that the individualistic-collectivist dichotomy results in some cultures being more open to working in geographically dispersed environments due to their levels of self-efficacy beliefs about virtual teamwork.

Collectivist cultures place the needs, beliefs, and goals of the team over the those of an individual [ 94 , 112 ]. Virtual teams characterized by collectivist culture are less likely to use CMC technologies [ 143 ]. When they do choose to adopt CMC technologies, collectivist teams tend to choose synchronous methods that provide high relationship-related informational value [ 143 ]. Informational value in this context refers to the extent to which CMC technologies convey information benefits team effectiveness [ 143 ]. Virtual teams that favor in-group members and accept perceptions of inequality are said to be characterized by “vertical collectivism” [ 254 ]. These teams are less likely to rely on CMC technologies, and are more likely to accept varying forms of informational value [ 143 ]. They are also more likely to employ asynchronous methods [ 143 ]. In contrast, teams that perceive equality amongst team members regardless of their role within the organization experience “horizontal collectivism” [ 253 ]. In this case, members of the team view themselves as being part of a collective and treat all team members as equal. [ 253 ]. While these teams are also likely to limit reliance on CMC technologies, they tend to require higher informational values and prefer synchronous methods [ 143 ].

In contrast to collectivist cultures, individualist cultures place the needs, beliefs, and goals of the individual over the those of an team [ 112 ]. Virtual teams with high levels of individualism are more likely to use CMC technologies, especially those that are high in task-related informational value, and tend to work asynchronously [ 143 ] Furthermore, team members from individualist cultures tend to communicate more openly and precisely [ 112 , 113 ] and are more willing to respond to ‘ambiguous messages’ [ 94 ], which is considered to be an indicator of trust [ 203 ]. This observation indicates that team members from individualistic cultures may be more ready to trust other teammates when communicating via technology than team members from collectivist cultures [ 123 ]. Thus, the issues and recommendations regarding technology and trust are applicable.

Teams with members that prioritize their own intrinsic and extrinsic goals while also favoring status differences are said to be “vertically individualistic” [ 156 ]. These teams are characterized by competitive members that are motivated to “win” [ 156 ]. In addition, while these individuals tend to belong to more in-groups than collectivists, they are not very emotionally connected to these groups [ 181 ]. Virtual teams with high levels of vertical individualism are more likely to adopt CMC technologies, tolerate varying forms of informational value, and will use asynchronous methods when required by superiors than teams characterized by horizontal individualism or any type of collectivism [ 143 ]. Team members with horizontal individualistic orientation prioritize their own self-interest while also viewing their teammates as equals [ 143 ]. Virtual teams with high levels of horizontal individualism are more likely to adopt CMC technologies, tend to require higher informational value, and will use synchronous methods when required by superiors as opposed to teams characterized by vertical individualism or any type of collectivism [ 143 ].

Socio-cultural diversity can also be characterized by the temporal orientation of their goals. Teams that focus upon the future and are willing to delay success or gratification for the purposes of future gain have a “long-term orientation” culture [ 143 ]. Cultures with long-term orientation tend to value perseverance, persistence, and focus on future-oriented goals [ 143 ]. In contrast, cultures characterized by “short-term orientation” are focused on the immediate needs of their teams with little consideration of the impact of their decisions on the future [ 143 ]. Virtual teams defined by long-term orientation are more likely to adopt asynchronous tools with high informational value and tend to be slower to rely on CMC technologies than short-term orientated teams, which prefer synchronous tools with low informational value [ 143 ].

Cultures can also be characterized by the amount of contextualizing is performed by an individual during communication [ 95 ]. For example, Japan, a high-context culture, relies more on the use of indirect communication via contextual cues (e.g., body language) to convey information [ 139 ]. Contextualization also affects choice of CMC technologies. High-context teams tend not to rely on CMC technologies and will prefer tools that high high informational value [ 143 ]. Low-context teams, in contrast, will rely on CMC technologies and will prefer those with low informational value [ 143 ].

Virtual teams are also affected by the levels of affectiveness/neutrality present in their culture. Affectiveness in this context refers to the amount of emotion that individuals usually express when they communicate [ 143 ]. For example, individuals from affective cultures such as Italy commonly exhibit their emotions publicly. [ 143 ]. In addition, individuals from affective cultures often feel that more neutral cultures (e.g., Japan) are more intentionally deceitful because they tend to hold back on their emotions [ 240 ]. Affective teams will be less likely to rely on CMC technologies and will prefer ones with high informational value [ 143 ]. In contrast, teams with neutral cultures will highly rely on CMC technologies and will prefer tools with low informational value [ 143 ].

Other types of socio-cultural diversity influence the performance of virtual team. For example, heterogeneity in the extent to which gender roles are traditional is positively related to team performance [ 70 ]. In a similar vein, heterogeneity in the extent to which there is discomfort with the unknown has a positive effect on issue-based conflict [ 70 ]. Uncertainty avoidance also affects tool use in virtual teams. Teams that have high amounts of uncertainty avoidance are more likely to use a synchronous CMC technology with high informational value. In contrast, teams with low uncertainty avoidance are unlikely to have a preference [ 143 ]. In addition to this, the degree of inequality that exists among members of virtual teams has an affect on the tools chosen for communication [ 143 ]. Teams with a high degree of inequality (i.e., high power distance) are more likely to use synchronous tools while teams with a low degree of inequality (i.g., low power distance) will prefer asynchronous tools [ 143 ]. Specificity also plays a role in virtual team performance. Someone from a specific culture (e.g., the United Kingdom) is more likely to view their coworkers as people with whom they only have a business relationship with, [ 87 ]. In contrast, more diffuse cultures (e.g., China) are more likely to view their teammates as friends and include them in their social lives [ 143 ]. This affects the choice communication methods employed by the team as teams characterized by high specificity are more likely to rely on CMC technologies than diffuse teams [ 143 ].

High socio-cultural distance is the cause of several types of collaboration problems. For example, high socio-cultural distance reduces communication and increases risk [ 2 ] caused by relationship breakdowns between distributed teams [ 250 ] and results in more processes challenges and lower team performance [ 86 ]. Socio-cultural distance also tends to worsen the way leaders sense, interpret, and respond to problems [ 271 ]. Cultural heterogeneity also tends to result in divergent subgroup identification [ 68 ] that may subsequently have a negative effect on team interactions and performance [ 67 ]. Furthermore, in accordance with similarity/attraction theory, team members attribute positive traits to team members that they believe are similar to themselves and prefer to interact with them [ 216 , 255 ]. Negative traits are thus associated with teammates that they believe are dissimilar from them and sometimes actively avoid interactions with those teammates [ 24 ]. As a result, the belief that others are different in terms of education, race, and attitudes (i.e., perceived diversity) is frequently associated with the negative consequences of team heterogeneity [ 100 ], such as unwillingness to cooperate and coordinate activities [ 56 , 117 , 148 ].

Furthermore, teams with high socio-cultural distance are more likely to have issues with integration and communication and have more conflict [ 269 ]. Both task and affective conflict are increased as a result of the differences in perspectives and approaches related to work, which further exacerbates differences in expectations, attitudes, and beliefs [ 195 , 204 ]. These differences in belief structures are particularly common in heterogeneous groups (i.e., groups with high socio-cultural distance) [ 268 ] which, in turn, increases conflict due to differences in interpretations and opinions of work processes [ 205 ]. Thus, there is a vicious cycle between differences in belief and intra-group conflict that is detrimental to collaboration.

The most commonly experienced problems correlating with socio-cultural distance are difficulties associated with diversity in language preferences, proficiency, and interpretation, which can create barriers for many projects [ 116 ], such as requiring increased effort [ 74 , 170 , 183 ]. This challenge is not just a matter of different languages, even native speakers of one language may have problems because of differences in dialects and local accents [ 33 ]. In many global collaborations, some (if not all) of the collaborators only speak English as a second language [ 132 , 219 ]. This situation causes problems when collaborators need to synchronously communicate via teleconferencing—these team members can become overwhelmed with trying to keep up with the conversation [ 132 , 219 ]. Furthermore, this language-based disadvantage can cause non-native speakers of the dominant language to feel alienated and as though they have a disadvantage when speaking [ 219 ]. Prior work has also shown that virtual teams whose members have different first languages have more conflict and lower levels of satisfaction and cohesion [ 238 ].

Misunderstandings can occur even in cases where all collaborators are fluent in a language if there are other differences in culture—a seemingly harmless joke could have a massively detrimental impact on the success of a project if it is misunderstood as an insult [ 250 ]. Olson and Olson observed one such misunderstanding where team members in the United States ended a video conference without expressing a ‘proper farewell’ to a European teammate [ 191 ]. In this case, the curtness was due to pressure on the American team, who were unaware of the cultural expectations regarding farewells, to cut costs by conducting short video conferences [ 191 ]. The European team, however, was unaware of this pressure and perceived the lack of a proper farewell as an insult [ 191 ]. Also, conflicts can arise when teammates from a culture where saying ‘no’ is considered impolite (even when saying ‘yes’ is a problematic answer) interact with teammates who do not share this compunction [ 116 ]. Treinen and Miller-Frost encountered an instance where collaborators from one culture did not ask many questions of their teammates and instead affirmed that they had a clear understanding of requirements, but were in reality too polite to express concerns [ 250 ]. In this situation, the other collaborators were unaware of this cultural difference and did not realize that their questions should not have formulated as ‘yes or no,’ but rather should have elicited responses that indicated understanding.

Other types of socio-cultural differences such as those caused by religion, generation, and doing orientation, can also affect virtual team success. Religious differences, for example, can make it difficult for team members to understand each others norms and traditions, which has a negative influence on collaboration [ 221 ]. Generational differences can affect how a team member responds to collaborating via CMC technology because not every has the high levels of technical expertise that makes them a “digital native” [ 129 ]. Finally, differences in the extent to which work is valued as a central life interest (i.e., “doing orientation”) is negatively linked to productivity [ 135 ]. However, differences in the extent to which team members have a sense of personal control over their work and life events are positively linked to team productivity, cooperation, and empowerment [ 135 ].

A review of literature reviews and meta-analyses suggests that the “main-effects” approach, where researchers focus on relationships between outcomes and diversity dimensions, ignoring moderating variables, cannot truly account for the effects of diversity [ 86 ]. The effect of socio-cultural diversity depends on other features of the team [ 272 ], such as how long members have interacted, the types of diversity investigated, and the types of outcomes under scrutiny [ 86 ]. High task complexity, high tenure, large team size, and low levels of geographic dispersion are found to moderate the effects of socio-cultural diversity on virtual teams [ 237 ]. Experience with CMC technology can also moderate socio-cultural diversity; high heterogeneity in technical experience heightens the negative effect that differences in nationality has on creativity [ 164 ]. Socio-economic variables (e.g., human development index (HDI)) has a significant impact on a country’s scientific production and collaboration patterns [ 118 , 152 , 199 ]. Kramer et al. found that socioeconomic similarities and economic agreements between countries have contributed to increased collaboration in the scientific field [ 143 ], which is likely to be virtual. The phase in which a virtual team is at in the project life-cycle affects assessment of team performance in culturally diverse teams. Culturally heterogeneous virtual teams will outperform culturally homogeneous teams during the later part of the project life-cycle [ 264 ]. This is likely a result of teams becoming more homogeneous over time as shared team values, associated norms, and identity enables the team to overcome process challenges that occur when team members encounter cultural differences [ 86 , 264 ].

Computer-mediated communication technology (e.g., email, video-conferencing) can reduce the negative effects of socio-cultural diversity early on in the life of a diverse virtual team due to their reductive capabilities [ 32 ]. In fact, use of these tools may even be beneficial for diverse teams for this reason [ 32 ]. Many issues regarding language barriers are surmounted by the use of asynchronous technology that allows workers to reflect and carefully consider their position before answering a question posed by a collaborator that primarily speaks another language [ 2 , 116 ]. These benefits result in the heavier use of asynchronous tools, which introduces the disadvantages of asynchronous tools (e.g., increased time and effort to effectively communicate, absence of important social information and nonverbal cues) [ 2 ]. Furthermore, asynchronous communication is not feasible in every situation. And, as discussed above, language barriers can cause problems during synchronous communication. Thus, developing technology that better supports synchronous communication across a language barrier is a promising opportunity for research in supporting collaboration.

Contradictions exist in the literature with regard to the effect of socio-cultural diversity on team performance. Edwards and Shridhar [ 66 ], for example, found no relationship between a team’s socio-cultural diversity and the learning, satisfaction, or performance of its members. Other research has suggested that socio-cultural diversity is unrelated to conflict [ 108 ]. Finally, Weijen found that whether or not members of a virtual team spoke English (specifically) did not have an influence on international collaboration, likely due to the pervasiveness of English as the default language for many international journals and indexed databases [ 259 ].

It is also recommended that the addition of basic cultural awareness [ 250 ] and language training [ 120 ] be incorporated into the beginning of every project to mitigate these issues before they become major problems. One specific suggestion is to employ some of the guidelines from agile development methodology (i.e., Scrum), such as daily status meetings, to mitigate the effect of assumptions by providing an opportunity to address issues or questions during the hand-off and allocation of tasks [ 250 ]. Given the plethora of tools developed for supporting Scrum (e.g., [ 209 , 229 , 251 ]), it would be interesting to see how these tools could be adapted to smooth over collaboration issues arising from cultural differences.

6.4.3 Work culture

Socio-cultural distance can be highly influenced by the work culture dimension. For example, there may be conflicts from high socio-cultural distance between two teammates from the same country that come from very different company backgrounds [ 8 ], while the opposite may be true of teammates with different cultural and national backgrounds who share a common work culture [ 2 ]. The success of a virtual team can hinge on factors such as differences in understanding with regards to processes and knowledge, institutional bureaucracy, status differences between team members, unworkable expectations reagarding shared goals and products, and conflicting or competing institutional priorities [ 54 ]. Power asymmetries in particular can create systemic bariers that need to be explicitly navigated (as opposed to expecting perfect process design will resolve them) [ 54 ]. While differences in work culture have the potential for stimulating innovation, proving access to richer skill sets, and sharing best practices, it also has the potential to cause misunderstandings [ 2 ] and communication breakdowns [ 14 ] between teammates. This influence is partly due to the difficulties associated with communicating subtl aspects of the team culture over distance (e.g., ‘how we do things around here’ [ 8 ]). For example, differences in the competitive or cooperative culture of a workplace can pose challenges [ 191 ]. Workers are less likely to be motivated to share their skills or ‘cover for each other (p. 1)’ in organizations or cultures that promote individual competition rather than cooperation. In contrast, cooperative cultures facilitate sharing skills and effort. This issue is particularly difficult to overcome in virtual teams.

Other differences in organizational structure and leadership can have a profound impact on successful collaboration in distributed groups. The characteristics of authority and authoritative roles vary across cultures [ 8 , 145 ] which can cause conflicts and undermine morale [ 2 ]. For example, [ 33 ] observed that in a collaboration between teams located in Ireland and the United States, the Irish workers required that authority figures earn their respect while the American workers were more likely to unquestioningly give respect to superiors. Another study that focused on a collaboration between teams in the United States and Europe had contrasting results [ 8 ]. Instead of the unquestioned respect found by Casey and Richardson, [ 8 ] saw that American workers were more confrontational with their superiors and verbally expressed objections and questions while the European teams had a more formal, hierarchical management structure. These differences indicate that support for differing work cultures needs to focus on the needs and conventions of the individual organizations and refrain from imposing standards based solely on the country in which the organization resides. The degree to which an organization allows autonomous decision-making afects relationships and behaviors between teammates and can inpact things like readiness to use technology in the collaboration or willingness to exchange knowledge [ 166 , 180 ].

Teams can also vary in their goals, norms, and incentives. A lack of alignment of incentives and goals as well as differences in expectations can pose very serious problems for a collaboration [ 191 ]. These misalignment’s are difficult to detect at a distance and require substantial negotiation to overcome [ 191 ], which is nontrivial using today’s technology. For example, collaborators may have different perceptions of time as a result of temporal discontinuities caused by differences in time zones, which may further reflect differences in the value systems of collaborators at each site [ 222 ]. Tensions may arise between workers at an American site that views time as a scarce commodity and perceives time as being something that can be spent, wasted, or lost, and collaborators at a Japanese site that view time as a cyclical, recurrent entity that is in unlimited supply [ 222 ]. Along with this finding comes different expectations with regards to how many hours a day team members are expected to work, or differing definitions of what it means to work hard [ 14 ], which often varies between countries [ 22 ]. These differences in expectations are particularly problematic when one team expects that another work more hours than they previously had been working [ 14 ]. Building a sense of shared goals and expectations happens more slowly in distributed groups [ 8 ], a process that could likely be assisted by the development of new communication technology. In addition, competing incentives can undermine a team’s performance [ 54 ].

Competitive funding models may affect willingness to collaborate and disincentivize team members to share skills, knowledge, and unpublished data [ 247 ]. For example, for the Collaborative Adaptation Research Initiative in Africa and Asia project, the core partners each created an individual grant agreement with the International Development Research Centre [ 54 ]. However, while the expectation was that partners would collaborate with each other, the partners were disincentivized to collaborate due to the individual grant agreements since the partners reported individually to the funding agency, rather than collectively [ 54 ]. Unfortunately, it is frequently unrealistic to expect these dynamics to resolve themselves in a short period of time and shift into an open and trusting relationship [ 54 ].

Expectations can be strongly influenced by the language used by different groups (e.g., ‘test procedure,’ ‘phase completion’) within a virtual team, sometimes creating animosity [ 8 ]. Language is further associated with methodology—for example, disparities in definitions of quality can be reflected in different assessment procedures [ 8 ]. Misunderstandings caused by differences in work practices and methodologies can affect coordination and cooperation [ 2 ], causing delays and conflicts [ 8 ]. In these situations, a common technical language must be developed to ensure understanding, which can be an extremely difficult task [ 15 , 122 , 172 , 252 ]. This need provides an opportunity for the development of technology to assist the creation and use of project-specific technical language.

In addition to differences in technical language, various groups within a virtual team may have different backgrounds that need to be reconciled, as different organizations within a group may have different expertise and experience that create incompatible views [ 55 ]. This issue is often unavoidable since one group may have specific knowledge necessary for the project to succeed [ 120 ]. Furthermore, differences in discipline and background have a stronger effect for distributed collaborations [ 211 ]. However, there are inconsistencies in the literature with regards to the effects of discipline on collaboration. Cummings and Kiesler, for example, found that field heterogeneity has a positive effect on distributed project success [ 50 ]. Specifically, they showed that projects including many disciplines had disclosed as many positive outcomes as did projects that involved fewer. However, in an earlier study, they found that projects incorporating many disciplines were less successful than projects that relied on fewer disciplines [ 133 ]. Thus, it is uncertain as to which conclusion is accurate, presenting open questions.

The way that administrative communication is managed [ 250 ] and tasks are allocated can play a big role [ 8 ] in the success of a virtual team. For example, a project manager could assign tasks differently and adjust the way that he or she communicates with management in accordance with the team’s culture and nationality [ 8 ]. Collaborations can further benefit from creating structured understandings about how to best work together by establishing expectations and definitions to undercut assumptions [ 8 ]. The challenge then becomes finding ways to develop technology that supports these structures while still facilitating innovation, ingenuity, and ‘rapid response to organizational threats or opportunities’ [ 64 ]. However, there are also inconsistencies between studies exploring the effects of work culture on collaboration. While Walsh and Maloney [ 261 ] stated that remote collaborations did not experience more work culture problems than co-located teams, McDonough et al. [ 170 ] found that differences in work culture and practices resulted in management problems in virtual teams. This disparity presents another open question.

7 Summary of findings and open questions

In this literature review, the major factors and challenges that impact collaboration in virtual teams were identified. Section  5 discussed distance factors (geographical, temporal, and perceived distance) and their associated challenges, including reduced motivation and awareness and difficulty establishing trust. In addition, barriers to informal and face-to-face communication, particularly the team’s technical competence and access to the appropriate technical infrastructure as well as prevalence of intra-team conflict were reviewed. Additional factors that particularly affect distance collaborations were outlined in Sect.  6 , namely the nature or coupling of the work, the need for explicit management, the configuration of dispersed sites and intra-team diversity along the dimensions of common ground, socio-cultural distance, and work culture. Several open questions and directions for future research were identified in the process of conducting the review; these are divided into questions of theory, questions of technology, and recommendations for future research. These findings are used to create design implications for the development of groupware targeted towards virtual teams later in Sect.  8 .

7.1 Questions of theory

7.1.1 should future research pursue ‘awareness’.

There is currently disagreement within the community as to whether or not ‘awareness’ should be taken as a conceptual approach to investigating collaboration challenges. Critics of ‘awareness’ describe the term as ‘ambiguous and unsatisfactory’ [ 224 ] and point towards it’s tendency to be paired with an adjective (e.g., ‘passive awareness’ [ 62 ]) in an attempt to lend some specificity [ 224 ]. Despite this, the awareness approach is still a commonly explored method [ 7 , 134 ], which suggests that there is a research opportunity to address this controversy.

7.1.2 Are coordination costs higher in teams that are temporally distributed?

There is also a lack of consensus within the community as to whether coordination costs are higher in teams that are temporally distributed. For example, while Espinosa and Carmel [ 73 ] state that coordination costs are reduced when team members are not working concurrently because no direct coordination takes place when the two teammates are not working at the same time, Ågerfalk et al. [ 2 ] and Battin et al. [ 11 ] assert that temporal distance significantly increases the cost and effort of coordination due to the added difficulties of dividing work across multiple time zones.

7.1.3 How do the disparities in levels of conflict and trust between balanced and imbalanced teams affect collaboration?

As previously discussed, levels of conflict and trust differ between balanced and imbalanced teams [ 188 , 210 ]. Specifically, subgroups in balanced teams experience weaker effects from faultlines on conflict and trust than large subgroups in imbalanced teams [ 210 ]. However, the ramifications are of these differences in trust and conflict are unknown, suggesting an opportunity for research.

7.1.4 Does tightly coupled work have a negative or a positive effect on collaboration?

Several studies [ 72 , 191 , 193 ] suggest that that tightly coupled work hinders distance collaboration. However, [ 15 ] found that tightly coupled work required collaborators to frequently interact to do their work and, as a result, forced these collaborators to know more about each other, help each other, and cultivate strong engagement despite being at geographically distant sites—which actually helps distance collaboration. Given the contrast between these conclusions, there is an opportunity for further research to investigate the effects of tightly coupled work, particularly in domains other than global software development.

7.1.5 What effect does geographic dispersion have on task and affective conflict?

Contradictions exist in the current literature as to the effect of geographic distance on affective and task-based conflict. Specifically, [ 179 ] found no significant difference in affective and task-based conflict between co-located and distributed teams. This, however, is in direct conflict with their later work [ 108 ]. These contradictions are particularly interesting given that the participants in both studies did research and product development, and are therefore directly comparable. It is therefore uncertain as to which conclusion is accurate.

7.1.6 Does background heterogeneity have a positive or a negative effect on collaboration?

This question is also currently unresolved, given the contradictions in literature. In 2002, Kiesler and Cummings found that projects incorporating many disciplines were less successful than projects that relied on fewer disciplines [ 133 ]. However, later they found that field heterogeneity has a positive effect on distributed project success [ 50 ].

7.1.7 Do virtual teams encounter more work-culture related problems than co-located teams?

This is yet another example of the community’s lack of consensus on issues surrounding collaboration. For example, while McDonough et al. [ 170 ] found that differences in work culture and practices resulted in management problems in virtual teams, Walsh and Maloney [ 261 ] stated that remote collaborations did not experience more work culture problems than co-located teams.

7.2 Questions of technology

7.2.1 how can we better support communication in temporally distant work.

Due to the differences in work schedule caused by differences in time zones, particularly when sites do not have overlapping workdays, distance workers rely on asynchronous technology (e.g., email, fax) to communicate with their collaborators. However, this method has several drawbacks. Asynchronous tools tend to increase the amount of time that a collaborator has to wait for a response [ 2 ] and can leave the recipient feeling overwhelmed by the number of asynchronous messages left during the previous night [ 19 ]. Moreover, the process of writing ideas in emails increases the risk of misunderstandings between collaborators [ 57 ] over talking in person or via the telephone.

7.2.2 How can we better support informal communication?

There is an additional challenge associated with communication technology in that there is insufficient support for determining a collaborator’s availability for spur-of-the-moment, informal communication [ 101 ]. This drawback, in particular, hampers informal communication that would otherwise happen during chance encounters in a co-located environment.

7.2.3 How can we design technology to assist in the development of trust?

Research shows that body language, subtle voice inflections, facial expressions, etc., which are notably more difficult to convey via communication technology, are essential to the development of trust [ 20 , 193 ]. Furthermore, communication technology is frequently used in an irregular, unpredictable, and inequitable manner, which hampers trust [ 123 ]. As a result, it is clear that current technology needs to be updated to better assist the development of trust in distance collaborations.

7.2.4 How do we support explicit management in teams that reject formal administration?

Explicit management is necessary for successful distributed, collaborative work [ 193 ]. However, some particular types of collaboration, such as research collaborations consisting mainly of scientists, avoid the application of explicit management in their projects [ 193 ].

7.2.5 How can we support synchronous communication across language barriers?

Language barriers are of significant concern in collaborations where collaborators have different socio-cultural backgrounds (i.e., speak different languages) [ 116 ] or different work backgrounds (i.e., use different jargon) [ 8 ]. In these cases, asynchronous communication allows collaborators to reflect before responding to each other, giving them a chance to look up unfamiliar terminology or become familiar with new ideas. However, asynchronous communication has several drawbacks, as mentioned earlier, and is not feasible in every situation.

7.2.6 How do we develop technology that supports structures for negotiating terminologies and methodologies while still facilitating flexibility?

Along with the issue of surmounting technical language barriers in synchronous communication comes the need to create and use a common technical language to ensure understanding in meaning and methodology. The development of a project-specific technical language is not an easy task [ 17 , 55 , 172 , 252 ], but is important enough to collaboration to warrant assistance from technology. It is also important to ensure that this technology is flexible enough to withstand changes that may be made to the project.

7.2.7 How can we leverage existing tools developed for supporting Scrum to mitigate problems caused by cultural differences?

It has been suggested that distance collaborations employ guidelines from agile development methodology, such as daily status meetings, to mitigate the effect of incorrect assumptions caused by socio-cultural or work culture differences. The existence of a vast number of tools developed specifically to assist Scrum (e.g., [ 209 , 229 , 251 ]) presents an opportunity to investigate how these technologies can be adapted to mitigate collaboration issues arising from cultural differences.

7.2.8 How can we design communication technology to support building a sense of shared goals and expectations?

Variances between times with regards to goals, norms, incentives, and expectations can pose very serious problems for a collaboration [ 191 ]. Overcoming these differences by building a sense of universal goals and standards is a slow, but vital, process for distributed groups [ 53 ]. Furthermore, these types of misalignments are hard to recognize in distance collaborations and require substantial negotiation to overcome [ 191 ], which is nontrivial given the limitations of today’s technology

7.3 Recommendations for future research

Siebdrat et al found that perceived distance was more strongly affected by a team’s national heterogeneity than by their spatio-temporal distance, and subsequently asserted that perceived distance is more indicative of collaboration challenges than spatio-temporal distance [ 231 ]. However, other work has demonstrated that distance can affect collaborators that are all in the same country at a single site [ 4 ], with low national heterogeneity and low spatio-temporal distance. Despite this, it is unclear whether perceived distance was high or low in this case due to the context of the study. Given the apparent influence of distance on collaboration, whether it is perceived, temporal, or spatial, it is therefore important to gain a better understanding of the relationship between these types of distance and their effects on collaboration.

8 Implications for design

This section uses the findings of this LR to address the final question, Research Question 2: How can we design technology for supporting virtual teams? To do so, the following four design implications for the development of groupware that supports collaboration in virtual teams are outlined.

8.1 Assist creation of common ground and work standards

Virtual teams consisting of workers with different expertise and organizational backgrounds require conversations about project-specific technical language, methodologies, and best practices. Technology should expedite and document these conversations and decisions to both create and facilitate the everyday use of technical language. Furthermore, since systems often incorrectly assume a shared knowledge of information [ 1 ] as recommended by [ 192 ], systems should document in a manner that allows users to search for abstract representations of information. Moreover, since methodologies, best practices, and technical language tend to evolve over time, this technology needs to also support the resulting negotiation and discussion processes, as opposed to only facilitating the initial decision-making process.

8.2 Facilitate communication

Both rich discourse (i.e., containing social information and nonverbal cues as well as words, typically provided by face-to-face communication), and spontaneous, informal communication have been identified as key to preventing conflict and improving trust in virtual teams. Thus, it is imperative that technology is designed to provide the benefits of face-to-face conversations (e.g., video conferencing), such as ease in immediately detecting confusion. This is important not only for synchronous communication but also asynchronous conversations since those are the most likely to have misunderstandings that could be mitigated with additional non-verbal information. Mechanisms for supporting informal communication (e.g., chance encounters) is similarly necessary. In addition, given the difficulties experienced by virtual teams where workers are required to speak in a language that is not native to them, it is important to consider means for supporting synchronous communication across language barriers.

8.3 Provide mechanisms for work transparency

One of the key challenges faced by virtual teams is feeling a sense of connectedness to the rest of the team. This is both due to the motivational effects of not feeling isolated and the increased effort required to feel heard and acknowledged by the rest of the team located at another site. Thus, technology should be designed to provide transparency that allows workers to feel aware of their teammates, Furthermore, this technology should highlight and encourage the contributions of an individual and boost visibility within the team.

However, technology that promotes transparency, particularly technology that creates the sense of a shared workspace through open video connections, should be wary of infringing on the privacy of the team since the more information a person sends, the greater the impact on one’s privacy [ 119 ]. Furthermore, the more information a person receives, the greater the chance of disturbing work [ 119 ]. Thus, it is important to reach a good balance between providing awareness and preserving privacy and limiting distractions.

8.4 Design lightweight, familiar technology

Technical infrastructure varies across organizations—teams may not have the resources to support data-heavy communication tools, limiting their access to sophisticated collaboration technology (e.g., multiplane video conferencing). Furthermore, infrastructure may even vary within a virtual team, limiting tool use for the entire group since it is important that communication capabilities be evenly distributed [ 193 ]. Thus, care should be taken to engineer technology that is as lightweight as possible, maximizing the number of potential users. Virtual teams also face challenges related to the technical competence of their team members. It is therefore recommended that designers create technology with enough similarities to the technology currently employed by the team to facilitate adoption. New technology also needs to be compatible with existing tools, to promote adoption [ 194 ].

9 Conclusion

This literature review provided an overview of the collaboration challenges experienced by virtual teams as well as current mitigation strategies. This review utilized a well-planned search strategy to identify a total of 255 relevant studies, which chiefly concentrated on computer supported cooperative work (CSCW). Using the selected studies, we described challenges as belonging to five categories: geographical distance, temporal distance, perceived distance, the configuration of dispersed teams, and diversity of workers. Findings also revealed opportunities for research and open questions. Finally, opportunities and implications for designing groupware that better support collaborative tasks in virtual teams was discussed through the description of four design implications: assist the creation of common ground and work standards; facilitate communication; provide mechanisms for work transparency; and design lightweight, familiar technology.

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Morrison-Smith, S., Ruiz, J. Challenges and barriers in virtual teams: a literature review. SN Appl. Sci. 2 , 1096 (2020). https://doi.org/10.1007/s42452-020-2801-5

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Article contents

Virtual teams and digital collaboration.

• Conny H. Antoni Conny H. Antoni Trier University
• https://doi.org/10.1093/acrefore/9780190236557.013.881
• Published online: 22 March 2023

Collaborating in teams by using various digital information and communication technologies (ICTs) to perform interdependent tasks and achieve common goals relevant for one’s organization is increasingly the new normal. Such more or less virtual teams—which can be all human or human-agent teams (HATs) (i.e., including autonomous software agents with artificial intelligence)—are complex dynamic open socio-digital systems embedded in an organizational, economical, and societal context. How and to what degree team members use ICTs to perform their tasks and to manage situational demands influence team processes and emergent states, such as transactive memory systems and team mental models, and thus team effectiveness. Research on input-mediator-output-input models of teamwork has shown that these processes are reciprocal, influencing team development over time. Research on virtual team effectiveness shows negative effects of virtual teams on team functioning and effectiveness primarily when short-term laboratory teams are studied, whereas no or lower effects were found for long-term organizational teams. These results have practical and theoretical implications, such as to support the launch of virtual teams by team-building interventions and trainings and to prefer longitudinal and field studies to examine processes and outcomes of virtual human teams as well as HATs.

• virtual teams
• human-autonomy teaming
• human-agent teams (HAT)
• information and communication technologies (ICTs)
• shared mental models
• social presence
• media richness theory
• media synchronicity theory

Relevance of Virtual Teams and Digital Collaboration

Modern information and communication technologies (ICTs), such as email, chat, video conferencing, augmented and virtual reality, and collaboration software with shared networked databases, enable synchronous and asynchronous communication and information access in real time and digital collaboration within and across locations, countries, and company boundaries. Members of virtual teams can be geographically dispersed but still coordinate with other team members and quickly access the same information. Especially for organizations operating in a global market, it has been crucial to take advantage of the opportunities of virtual teams. Specialists for complex and customer-specific project tasks can be recruited across the world more easily and contribute their knowledge to different teams working in parallel as needed. Thus, digital collaboration promises companies organizational flexibility and acceleration of work processes. Furthermore, employees may benefit from more flexible work arrangements granting more autonomy to decide where and when to work, reducing commuting time and costs when working from home. Already in the 1990ies, virtual teams were announced as the new way to work and the peopleware of the 21st century ( Lipnack & Stamps, 1997 ). Although many knowledge workers had already been collaborating digitally (at least to some extent) for a long time, the beginning of the covid pandemic in 2020 was a game changer. Almost from one day to the next, offices were shut down and people worked from home. Collaborating digitally became the new normal. Companies and employees that had no experience with virtual teams realized the chances and risks of virtual teamwork and digital collaboration. After the forced experience, companies and employees seem more willing to continue virtual teamwork than before. In the future, digital collaboration will increasingly encompass software agents, which can act and decide autonomously based on artificial intelligence ( O’Neill et al., 2022 ). Only time will tell if the vision of human team members and software agents meeting in the metaverse via avatars will come true.

The focus of this article is on virtual teams and digital collaboration in teams. Virtual team research deals with phenomena and questions on the team level, such as how working with collaborative ICT affects the emergence of trust between members or influences the relationship between team processes and outcomes. In contrast, telework and telecommuting research focuses on the individual level of analysis, such as on the relationship between individual characteristics and individual adjustment, well-being, and performance comparing office work with non-office contexts using individual and mobile technologies ( Raghuram et al., 2019 ). The structure of the article is as follows. First, I define the concept of virtual teams and team virtuality. Then, I describe the factors influencing the processes and the development of emergent states and outcomes of virtual teams using an input-mediator-output-input (IMOI) model of team effectiveness before deriving practical implications and future research perspectives.

Defining and Measuring Team Virtuality

Lipnack and Stamps (1997) define a virtual team, like any team, as “a group of people who interact through interdependent tasks guided by common purpose” but which “works across space, time, and organizational boundaries with links strengthened by webs of communication technologies” (p. 7). The authors combine aspects of ICT-mediated communication and distributed work with core aspects of a definition of teams in general. However, the mentioned aspects of teams in general might also apply for people working interdependently along a process chain in different departments or even companies. Hence, this definition might fit for digital collaborative work better than for virtual teams. To differentiate teamwork from collaborative work in general core aspects are missing, such that teams have specific common goals linked to organizational goals and members have different roles and responsibilities for attaining them ( Kozlowski & Ilgen, 2006 ). Teams have boundaries and linkages to the broader system context and task environment and are—apart from cross-organizational project teams—embedded in an encompassing organizational system.

With respect to team virtuality, Schulze and Krumm (2017) point out that at least four different types of definitions of virtual teams exist in the literature: (a) definitions treating virtual and face-to-face teams as a dichotomy; (b) definitions based on a single dimension of team virtuality, ranging from low (merely face-to-face) to high (entirely virtual) virtuality; (c) definitions with multiple dimensions of virtuality; (d) definitions which emphasize how individuals perceive and react to discontinuities in which routine behaviors do not produce expected effects (e.g., Watson-Manheim et al., 2012 ).

Approaches using multiple dimensions differ in terms of facets and measurement. For example, Chudoba and colleagues (2005) consider the aspects of geographic locations, time zones, cultures, work practices, organizations, and ICTs as potential discontinuities. They asked team members to rate these aspects (e.g., how often team members experienced working with people at different sites). They used a factor analysis to develop a three-dimensional measure of team virtuality encompassing team distribution, workplace mobility, and variety of work practices. Others, such as Gibson and Gibbs (2006) , use objective indicators to measure team distribution and combine them with external or team members’ ratings on electronic dependence, dynamic structure, national diversity, and psychological safety. Criteria such as dynamic structure, national diversity, and psychological safety apply also to merely face-to-face teams. They can be used to differentiate between teams in general but appear less suited to define team virtuality. Therefore, most definitions of team virtuality focus on geographic dispersion and technology use ( Gilson et al., 2015 ).

Geographic dispersion implies that team members cannot interact face-to-face besides when meeting in person or using videoconferencing tools. However, digital collaboration can also take place to varying degrees when team members are co-located. Focusing on ICT use and characteristics might therefore tap the core of team virtuality. For example, Kirkman and Mathieu (2005) define team virtuality as the extent to which team members use virtual tools to coordinate and execute team processes, the amount of informational value provided by such tools, and the synchronicity of team members’ virtual interaction. By integrating informational value and media synchronicity as criteria for team virtuality, they build on media richness theory ( Daft & Lengel, 1984 , 1986 and media synchronicity theory ( Dennis et al., 2008 ), which explain how ICTs influence information and communication processes in organizations.

Handke and colleagues (2021) introduce the concept of team perceived virtuality. They describe team perceived virtuality as an emergent state influenced by structural team virtuality and other team characteristics and team processes, which in turn influence team outcomes. Team perceived virtuality consists of two dimensions: collectively experienced distance and collectively experienced information deficits. However, by focusing on these two dimensions, they adopt only a deficit-oriented view, implying that increasing team virtuality means more distance and information deficits, leaving out any positive effects, such as increased flexibility.

Furthermore, the above-described definitions of virtual teams focus implicitly on human teams. However, the rapid development of artificial intelligence allows researchers and developers to design software agents with higher levels of agent autonomy and to integrate them in digital collaboration and virtual teams. O’Neill and colleagues (2022 , p. 911) define human-autonomy teams or human-agent teams (HATs):

as interdependence in activity and outcomes involving one or more humans and one or more autonomous agents, wherein each human and autonomous agent is recognized as a unique team member occupying a distinct role on the team, and in which the members strive to achieve a common goal as a collective.

To be considered autonomous, the agents must meet at least partial levels of self-directed behavior (agency) and agent autonomy. The concept of levels of automation was suggested by Parasuraman and colleagues (2000) and ranges from low (level 1: agent offers no assistance) to high (level 10: agent decides everything). Partial agent autonomy means that the computer can at least suggest and execute actions and decisions if they are approved by the human (level 5) or do not veto actions and decisions before they are automatically executed (level 6). Whether one perceives an autonomous software agent as a virtual teammate or collaborator or as a machine with artificial intelligence performing collaborative tasks might also depend on the similarity of perceived agent personality characteristics to the individual ( Dryer, 1999 ). Boundaries might get more fluid in the future when humans and software agents interact via avatars in the metaverse and when software agents can recognize emotions and react accordingly ( Lee et al., 2021 ).

Integrating research on HATs and following Kozlowski and Ilgen’s (2006) definition of teams, I define virtual teams as two or more human or autonomous software agents who (a) collaborate to perform organizationally relevant tasks; (b) interact at least to a certain degree virtually to achieve one or more common goals; (c) are interdependent with respect to workflow, goals, and outcomes; (d) have different roles and responsibilities; and (e) are embedded together in an encompassing organizational system or cross-organizational agreement with boundaries and linkages to the broader system context and task environment. This definition implies that virtuality can have varying degrees and that different types of virtual interaction are used. Virtual teams with human members can vary the degree and type of virtual interaction over time depending on task and situational demands as well as human member needs. They can interact virtually exclusively or alternate virtual and face-to-face interaction or combine the two interactions. Most of the existing virtual teams have some face-to-face contact ( Hertel et al., 2005 ). Partially virtual teams, which alternate virtual and face-to-face interaction or combine them, with some team members interacting face-to-face and others virtually, are also called hybrid teams ( Hosseini et al., 2017 ). Virtual, digital, or e-collaboration is collaboration among individuals or autonomous software agents to accomplish common tasks using electronic technologies, which could happen even without interacting or communicating ( Kock, 2005 ), for example, by telework.

The facets used to define virtual teams are also used to define virtual organizations, where virtual teams are embedded and members collaborate digitally. For example, Ahuja and Carley (1999 , p. 742) define virtual organizations “as a geographically distributed organization whose members are bound by a long-term common interest or goal, and who communicate and coordinate their work through information technology.”

An IMOI Model of Virtual Team Effectiveness

To summarize virtual team research, I adopt an IMOI model ( Ilgen et al., 2005 ; Kozlowski & Ilgen, 2006 ). In comparison with an input-process-output model ( Hackman, 1987 ), an IMOI model emphasizes that virtual teams are complex dynamic open socio-technical or socio-digital systems embedded in an organizational, economical, and societal context ( Antoni & Hertel, 2009 ). Employees are organized in teams within or between organizations to contribute to organizational goals by achieving common team tasks and goals with the help of ICTs. Virtual team members (humans and autonomous software agents) learn and develop through the execution of their tasks and the use of ICTs. They have to adapt to changing internal and external situational demands, but their actions and performance in turn also contribute to organizational and situational changes. Important factors influencing team outcomes via team processes and the development of emergent states are ICTs and team tasks, team member characteristics, and situational demands as input factors. The IMOI model (see figure 1 ) describes the recursive and cyclical processes between inputs, mediators, and outcomes.

Figure 1. An input-mediator-output-input model of virtual team effectiveness.

Information and Communication Technologies

ICTs are important elements of the technical system of virtual teams as team members collaborate using ICTs. The characteristics of ICTs influence task and situational demands, team processes as well as the development and outcomes of virtual teams. But as virtual teams learn and develop, also the characteristics of ICTs can change. Key ICT characteristics or functionalities discussed in the literature are the degree of social presence, media richness, naturalness, and synchronicity.

Social presence means the degree to which one is aware of the other person in an interaction. Social presence theory proposes that media differ in their degree of social presence and that communication effectiveness depends on the task-media-fit. Face-to-face interaction is considered to have the most social presence, and text-based communication the least. For effective communication, the degree of social presence should have the level of interpersonal involvement required for a task ( Short et al., 1976 ).

Similarly, media richness theory states that media can be ranked according to their information richness. In their seminal article, Daft and Lengel (1986 , p. 560) defined information richness “as the ability of information to change understanding within a time interval.” They proposed that communication media differ in their capacity to transmit rich information because of the number of channels they use, the number of cues they can transmit in a given time, their capability for immediate feedback, personalization, and language variety. Using these criteria, they presented a hierarchical classification of media in order of decreasing richness: (a) face-to-face, (b) telephone, (c) personal documents such as letters or memos, (d) impersonal written documents, and (e) numeric documents ( Daft & Lengel, 1984 , 1986 ). Daft and Lengel argue that when working under bounded rationality and time constraints, organizations should use rich media to reduce equivocality and quickly clarify ambiguous issues to reach a common understanding of a situation. Videoconferences, telephones, and chat software were not available that time and could probably be ranked second, third, and fifth according to this logic. Kirkman and Mathieu (2005) suggest that subjective ratings of the amount of informational value might be better able to assess media richness than objective ranking as proposed by Daft and Lengel (1984) . Research supports that people perceive ICT functionalities differently and that intraindividual differences and differences between situational contexts occur over time and can influence performance (e.g., Carlson & Zmud, 1999 ; Fuller & Dennis, 2009 ; Hantula et al., 2011 ).

Why do team members perceive ICT functionalities differently and change their perception? Channel expansion theory suggests that the knowledge base of ICT users and their ability to communicate with an ICT develop with experience and change the perception of media richness ( Carlson & Zmud, 1999 ). Particularly, the experience of using a medium, the experience with communicating partners, and perceived social influence change the perception of media richness not only between and within users but also between situational contexts ( Carlson & Zmud, 1999 ; D’Urso & Rains, 2008 ; Hollingshead et al., 1993 ).

Similarly, adaptive structuration theory argues that people actively select how they appropriate and use the features of a technology and that this appropriation may change over time ( DeSanctis & Poole, 1994 ). In line with this reasoning that ICT use is a function less of physical properties than of media appropriation and perception, Handke and colleagues (2018) report findings that individuals change their perception of ICT richness over time and toward communication partners. Fuller and Dennis (2009) showed that while task-media/technology-fit predicted team performance when teams used a technology the first time, over time teams with an initial fit did not perform better than teams with an initial poor fit. In line with adaptive structuration theory, teams with an initial poor media/technology-fit innovated and adapted their ICT use and improved their performance. This indicates that it is not ICTs that determine the processes and performance of virtual teams but rather that it is a recursive relationship in which the two influence each other ( DeSanctis & Poole, 1994 ).

Although there is no technological determinism, ICTs influence media use, team processes, and outcomes. Media naturalness theory argues that people prefer media similar to face-to-face interactions because they require less cognitive effort for knowledge transfer because of the evolution of our brain ( Kock, 2004 ). Kock suggests that the degree of similarity or naturalness of media can be assessed by the co-location of people communicating, the synchronicity to exchange information quickly, the ability to convey and observe facial and body expressions, and, in particular, the ability to convey and listen to speech. Kock (2004) proposes that cognitive adaption to ICT and the degree of schema alignment between team members decrease the cognitive effort required.

The synchronicity of information exchange is the focus of media synchronicity theory ( Dennis & Valacich, 1999 ; Dennis et al., 2008 ). It differentiates conveyance and convergence of meaning in communication processes. Conveyance refers to the transmission and exchange of information between team members; convergence refers to the information processes needed for sense making to achieve a common understanding of the information received. Both processes are regarded as necessary for understanding tasks but differ in terms of the media synchronicity required. Media synchronicity can be defined as the extent to which media capabilities enable individuals to work together on the same activity at the same time and to have a shared focus ( Dennis & Valacich, 1999 ; Dennis et al., 2008 ). Media synchronicity theory proposes that a higher degree of media synchronicity is required for convergence than for conveyance processes. Consequently, it is proposed that the use of higher synchronic media will lead to better communication performance if team members want to achieve common understanding and, vice versa, that lower synchronic media are supposed to lead to better performance if teams want to convey information. Media synchronicity is determined by media capabilities to support information transmission and processing.

Dennis and colleagues (2008) propose that media synchronicity is supported by (a) the speed of media to transmit information (transmission velocity/channel capacity), (b) media with more natural symbol sets, allowing fast encoding and decoding, and (c) symbol sets better suited to the content of a message (e.g., vocal tone to show doubt); they propose that media synchronicity is impaired by (a) a higher extent to which signals from multiple senders can be transmitted simultaneously using a medium (parallelism), (b) messages that can be rehearsed before sending (higher media rehearsability), and (c) messages that can be reexamined during decoding (higher reprocessability) as shared focus is lowered.

Team Tasks, Team Members, and Situational Demands

Key input factors for virtual teams that influence teamwork interacting with ICTs are team tasks, team members, and situational demands. Virtual teams are formed to fulfill tasks relevant for an organization with the help of ICTs that cannot be effectively accomplished by individuals alone. Team tasks influence workflow and coordination demands and thus the structure and design of virtual teams. Team tasks define the minimum requirements that team members must meet in terms of knowledge, skills, attitudes, and other characteristics (KSAOs), such as dispositions or personality characteristics. Tasks are performed under certain situational conditions that pose specific requirements for team members. Moreover, situational conditions might change, and virtual teams have to cope with the resulting situational demands.

Which types of tasks are suited for virtual teams? Obviously, tasks requiring information processing and specialist knowledge, such as in research and development, are better suited for virtual teams than tasks requiring manual work. Furthermore, if these tasks are separable into subtasks, coordination requirements are reduced. However, subtasks have to be interdependent to some degree; otherwise, only digital collaboration but no virtual teamwork would be needed. Typically, project tasks that are unique and time-limited and require the integration of specialized knowledge for planning and problem solving are well suited for virtual project teams, particularly if the specialists needed are distributed locally ( Hertel et al., 2005 ). Although the time frame for a project task can vary considerably from months to years, all project teams have, by the very definition of a project, a fixed deadline to accomplish the task after which the teams are usually dissolved. Aside from purely project-based organizations, project team members continue to work in their functional job while working part-time in one or more project teams. Hence, project tasks usually imply multiple team membership ( Bell & Kozlowski, 2002 ; Margolis, 2020 ) in several more or less virtual project and functional teams. Larger projects are often organized as multi-team systems with interdependent project teams working together to achieve a common goal ( Shuffler & Carter, 2018 ; Zaccaro et al., 2020 ). However, multi-team systems to address larger problem-solving tasks are not restricted to projects. In particular, international companies use virtual multi-team systems to coordinate distributed functional teams and to develop, adapt, and implement global company strategies.

Team Members’ KSAOs

Team tasks determine what KSAOs are required from team members, and they are selected or have to be trained accordingly. As virtual teams perform their tasks using ICTs, team members require, besides task and team, ICT-specific KSAOs. Schulze and Krumm (2017) provide a review of the literature on KSAO requirements of team virtuality. They found that successful performance in virtual teams requires media-specific KSAOs; that is, team members should know about the functionalities of the media and use their potential, how and when to use a certain medium for communication and knowledge transfer, and be able to adapt to channel restrictions of certain media (e.g., when using emails as opposed to videoconferences). Besides having media-specific KSAOs, virtual team members should be able to communicate effectively with distributed team members (communication KSAOs), to act in a way that creates trust (e.g., by being responsive and dependable) and to be willing to trust others (trust-related KSAOs), to be able to work with people from different cultural backgrounds (intercultural KSAOs), to manage oneself effectively (e.g., self-, time-, and project-management KSAOs), and to handle conflicts constructively (conflict management KSAOs). These media-unspecific competences are particularly required when the available media are inappropriate for the team tasks or when team members work in different time zones and cultures.

Situational Demands

As virtual teams are complex dynamic open socio-digital systems embedded in an organizational, economical, and societal context, they have to learn to deal with changing situational demands and adversities. Whereas changes can be perceived as being positive, neutral, or negative (such as additional team tasks and responsibilities) and may require adaptation of task strategies and team processes, adversities have a negative connotation and are associated with disruption, stress, and failure ( Hartwig et al., 2020 ). Changes and adversities can originate from within the team or from outside. Internal adversities, such as the failure or the loss of a team member, or external adversities, such as a conflict with another team or a customer, require virtual teams to be resilient to deal with the adversities ( Raetze et al., 2021 ). This may or may not require virtual teams to adapt their task strategy and team processes.

Team Processes

In the IMOI model, team processes are mediators, which mediate the effects of team inputs on team outcomes. Team processes describe how team members interact and exchange information with or without ICTs to coordinate and monitor their taskwork. Taskwork describes what tasks teams are doing, their interaction with tasks, ICTs, and other technical tools and systems.

Team processes can be differentiated in transition, action, and interpersonal processes. Transition processes encompass team mission analysis, formulation and planning, goal specification, and strategy formulation. Team action processes are the monitoring of goal progress, systems, and team monitoring and coordination. Interpersonal processes include conflict and affect management as well as team motivation and confidence building ( Marks et al., 2001 ).

Team processes are dynamic. Over time, team interaction and information exchange, with or without using ICTs, shape team emergent cognitive and affective states, which in turn influence team processes as well as team outcomes, which reciprocally influence team processes and emergent states ( Kozlowski & Ilgen, 2006 ). DeChurch and Mesmer-Magnus (2010) provided support for this conception. Results of their meta-analysis of 65 independent studies show that both emergent cognitive and affective states were strongly associated with performance. Team cognition was significantly related to team affective states, such as team cohesion, and team action and transition processes, as well as to team performance. Team cognition, team cohesion, and team processes predicted team performance, and team cognition explained unique variance in team performance after controlling for team cohesion and team processes.

ICTs do influence team processes, as suggested by social presence ( Short et al., 1976 ) and media richness ( Daft & Lengel, 1986 ) theories. However, there is no technological determinism. As described above, people learn to appropriate new media by using them in virtual team interaction ( Fuller & Dennis, 2009 ), and this experience can change ICT characteristics by, for example, developing and learning to use emoticons in e-mails and instant messaging ( Carlson & Zmud, 1999 ).

Team Learning and Adaptation

Team learning is both a team process and an outcome ( Edmondson et al., 2007 ; Kozlowski & Bell, 2008 ). As a process, team learning can be defined as the interaction behaviors of team members to acquire, share, refine, or combine knowledge relevant to the team and the task. Team learning behaviors include the reflection of processes and outcomes, seeking feedback and information from outside the team, and storing and retrieving generated knowledge, encompassing transition, action, and interpersonal processes. As an outcome, team learning describes the acquisition of new knowledge, skills, and attitudes by team learning behaviors, which broadens the action repertoire of a team. Team learning is crucial for the appropriation of ICT functionalities in virtual teams and for team adaptation to ICT, team, and situation requirements ( Fuller & Dennis, 2009 ; Handke et al., 2018 ). Team learning and team adaptation are closely intertwined as team learning can be regarded as both an antecedent and an outcome of team adaptation.

Burke and colleagues (2006 , p. 1190) define team adaptation “as a change in team performance, in response to a salient cue or cue stream, that leads to a functional outcome for the entire team.”

Following this definition, team adaptation can be observed as it is manifested in the innovation or modification of actions or existing structures, while team learning can be latent as a change of new knowledge, skills, and attitudes if it is not implemented in actions. Thus, team learning is a necessary but insufficient condition for team adaptation. When teams adapt (e.g., to ICTs and change their ICT use), they may acquire new knowledge, skills, and attitudes because of team adaptation. Oertel and Antoni (2014) showed that interruptive events can trigger team adaptation via reflective team learning. However, depending on the phase of team development, different team learning behaviors may be relevant for changing team knowledge structures. Research indicates that knowledge-based processes (storage and retrieval) play a more important role during early stages of project-based teamwork, followed by a shift to a higher relevance of communication-based processes (reflection and co-construction) in later stages ( Oertel & Antoni, 2015 ).

Team Leadership

Bell and Kozlowski (2002) argue that team virtuality (i.e., spatial distance and ICT-mediated communication) impedes two primary team leader functions (i.e., team performance management and team development). They recommend delegating these functions to the team and implementing team self-regulation processes using team goal and feedback systems ( Kozlowski & Ilgen, 2006 ). Feedback is important not only regarding key performance indicators to coordinate taskwork but also regarding social processes to support team coordination and team cohesion, motivation, and development ( Hertel et al., 2005 ). For example, Ellwart and colleagues (2015) showed that individual online feedback about individual information overload perceptions and task knowledge followed by collective team reflection increased situation awareness and supported virtual team adaptation processes. Self-regulating teams also require shared leadership. Several studies support the positive relation between shared leadership and virtual team performance ( Hoch & Kozlowski, 2014 ). However, studies report inconsistent results regarding the effects of transformational leadership and virtual team performance. Some studies report negative effects ( Gilson et al., 2015 ; Hoch & Kozlowski, 2014 ), others positive effects ( Avolio et al., 2014 ; Kahai et al., 2013 ; Purvanova & Bono, 2009 ).

The Development of Team Emergent States

Closely related to team processes is the development or emergence of cognitive and affective states, such as trust, transactive memory systems (TMSs), and shared mental models (SMMs), as well as team motivation and affective states, such as team cohesion. Team emergent states and team processes interact and mediate the effects of team inputs on team outcomes.

When a virtual team starts from scratch, team members do not know each other or what is expected from them as a team and from each team member. Team members have to get to know each other. They have to agree on their team tasks and goals as well as on their task strategies and roles before they are able to coordinate and perform effectively. Most authors agree that it is more difficult to get started as a team, to learn each other’s expectations and KSAOs, and to develop team trust only by using ICT-mediated communication. Therefore, they recommend kick-off workshops face-to-face to get to know each other, to clarify tasks and goals as well as team member roles and functions, and to develop rules for virtual teamwork and mutual trust ( Hertel et al., 2005 ). Particularly, the development of trust seems to be both a challenge and a requirement for virtual teams.

Team trust can be defined as an emergent shared willingness of team members to be vulnerable to the actions of the other team members, which are important to the team, irrespective of the ability to monitor or control them ( Breuer et al., 2016 ). A meta-analysis of 48 field and six laboratory studies using cross-sectional (34 studies) and longitudinal (24 studies) data shows that the relationship between team trust and team task performance was stronger in virtual than in face-to-face teams ( Breuer et al., 2016 ). Team trust was also significantly related to information processing (knowledge sharing and team learning), contextual performance (e.g., showing extra effort, volunteering, helping and cooperating with others, following organizational rules, and defending organizational goals), and team attitudes, such as team cohesion, satisfaction, commitment, and effort. However, the studies were too few and the sample size was too low to test whether virtual teams differ from face-to-face teams with respect to these variables. Also, cross-sectional studies, same source data, and subjective ratings showed stronger (and significant) relationships compared with studies using longitudinal data, different data sources, and objective data. Nevertheless, these results are in line with the authors' reasoning that when team members trust each other, they are more likely to take the risk to share their knowledge thus supporting team effectiveness via team coordination and cooperation. As practical implications, the authors recommend, besides trust-building activities, documenting team interactions particularly in virtual teams because their results indicate that the need for trust in virtual teams decreases when interactions in teams are documented. They assume that documenting team interactions facilitates peer monitoring and allows reviewing and verifying team agreements and decisions and thus reduces the risk that individual team members think their efforts are exploited by others.

Transactive Memory Systems

Virtual teams are often implemented to solve project tasks, which require the knowledge and collaboration of different specialists. The concept of TMS is highly relevant for explaining team coordination and performance of this type of teams because it explains how teams can use the individual memories and the distributed specialized knowledge of their team members efficiently. The TMS concept combines two components: (a) a transactive memory that connects the knowledge held by each team member to the knowledge held by the others and (b) knowledge-relevant transactive communication processes that occur among group members ( Wegner, 1987 ). In order to encode, store, and retrieve distributed specialist knowledge, teams need a shared transactive memory or metaknowledge of expertise location (knowing who knows what). Metaknowledge is defined as the shared perception of expertise location (i.e., the shared knowledge of the expertise and knowledge domains of the other team members). Research on TMS shows that individual team members can function as distributed knowledge repositories, each specializing in particular areas of knowledge and expertise to extend the knowledge capacity of teams and to improve team performance by the cognitive division of labor ( Ren & Argote, 2011 ). Many studies showed that memory specialization, task credibility, and task coordination in teams improved team coordination and performance ( Lewis, 2003 , 2004 ; Liang et al., 1995 ).

Shared Mental Models

While the TMS concept focuses on how teams can profit from team members with specialized and distributed knowledge, the concept of SMMs explains how shared cognitions about work-relevant aspects allow implicit coordination and enhance task performance ( Cannon-Bowers et al., 1993 ; DeChurch & Mesmer-Magnus, 2010 ). SMMs emerge in a dynamic process of convergence and divergence of individual mental models in team interaction and communication processes and manifest as emergent states in teams as a higher-level, collective phenomenon ( Kozlowski & Klein, 2000 ). Whether teams collaborate face-to-face or via ICTs influences and impedes the development of SMMs ( Andres, 2011 , 2013 ).

SMMs can be described in terms of similarity and accuracy. Similarity measures the extent of match between individual team members’ mental models. Accuracy describes the extent to which the team members’ SMMs correspond to standards, rules, and expert assessments ( Mohammed & Dumville, 2001 ).

Cannon-Bowers and colleagues (1993) initially differentiated four types of mental models: the equipment, task, team interaction, and team mental model. They suggested that particularly task (e.g., task procedures), team interaction (e.g., roles and role interdependencies), and team mental model (e.g., teammates’ abilities and preferences) across tasks and situations should be shared in teams.

While the task and interaction mental model were considered as moderately dynamic and the team model as highly dynamic, the equipment mental model was regarded as highly stable across tasks and situations. Cannon-Bowers and colleagues (1993) assumed that equipment mental models (the knowledge of equipment functioning and limitations, operating procedures, and likely failures) focus on individual taskwork and do not need to be shared. Although later research integrated task and technology/equipment aspects in the concept of task mental models and team and team interaction aspects in team mental models ( Mathieu et al., 2000 ), equipment aspects were neglected in research for a long time.

In the face of the multitude of collaborative ICTs that support the interaction and coordination of virtual team members, researchers called for considering ICT SMMs ( Schmidtke & Cummings, 2017 ). Müller and Antoni (2020 , 2022) showed that a shared understanding of ICT functionalities, task-specific ICT use, ICT adaptation, and ICT netiquette within a team had an impact on virtual team coordination and performance via team communication. Results also indicated that information about the advantages and disadvantages of ICTs can influence ICT mental models and that explicit planning of ICT use contributes to ICT SMM similarity ( Müller & Antoni, 2022 ).

Furthermore, it has been shown that a temporal SMM, defined as shared knowledge about deadlines, pacing, and sequencing of tasks, contributes to team coordination and performance ( Gevers et al., 2006 ; Mohammed et al., 2015 ).

Team Motivation and Team Affective States

Several studies showed that team motivation and team affective states, such as team cohesion, can be impaired if team members interact only virtually, because feelings of anonymity and low social control might support social loafing. On the other hand, team motivation and cohesion are considered crucial for virtual team functioning and performance ( Hertel et al., 2005 ). Study findings indicate that positive team affective tone is positively and negative affective tone is negatively related to team cooperation and indirectly to team performance ( Lin et al., 2017 ).

Team Outcomes

Team outcomes are often conceptualized as team effectiveness encompassing multiple dimensions and perspectives, such as team performance as evaluated by different stakeholders, team satisfaction (i.e., the satisfaction of team members with their team), and team viability (i.e., their willingness to continue work together as a team).

Impact of Team Virtuality on Team Effectiveness

In their meta-analysis of 428 samples from 398 studies on the relationship between team design characteristics and team performance, Carter and colleagues (2019) found only a very small negative relationship (r = −0.05) between team performance and dispersed and virtual teams. This finding does not support the results of prior studies and predictions of social presence theory ( Short et al., 1976 ) and media richness theory ( Daft & Lengel, 1984 ) described above. For example, Baltes and colleagues (2002) had reported results of their meta-analysis of 27 studies and 52 effect sizes that computer-mediated communication decreased group effectiveness and member satisfaction and increased time required for task completion compared with face-to-face teams. Lim and colleagues (2007) reported in their meta-analysis of 33 laboratory studies with 62 data points that virtual teams needed more time to reach a decision but achieved higher decision quality, but the authors did not find differences in terms of decision satisfaction between virtual and face-to face teams.

Ortiz de Guinea and colleagues (2012) analyzed 80 data sets from 79 studies and reported negative effects of virtual teams compared with face-to-face teams on team functioning: virtual teams had more task conflicts, lower communication frequency, and less knowledge sharing, and lower performance. The effects for task conflicts, knowledge sharing, and lower performance were stronger for short-term teams than for long-term teams. However, long-term teams had more relationship, process, and other conflicts and a lower communication frequency than short-term teams. Interestingly, in studies with continuous measures of virtuality, they found that the relationship with task conflict was more negative (i.e., lower conflict for more virtual teams) and that the relationships with knowledge sharing and satisfaction were more positive, and they found no association with performance. Other meta-analyses found positive effects of virtual teams compared with face-to-face teams. For example, compared with face-to-face teams, virtual teams generated more ideas, needed less time for task completion, and team members were more satisfied, if there was a fit between the group support system and the task and if the group received appropriate support ( Dennis et al., 2001 ).

Also, Fjermestad (2004) reports an increased number of ideas generated in teams using synchronous group support systems, while no differences were observed between face-to-face teams and teams using synchronous group support systems with respect to satisfaction and usability. However, face-to-face teams showed higher levels of consensus and perceived quality, communicated more, and required less time to complete the tasks. Similarly, Rains (2005) reports that teams using synchronous group support systems generated a larger number of unique ideas and experienced less member dominance than face-to-face teams.

Purvanova and Kenda (2022) criticized studies that reported negative relationships between virtuality and team effectiveness because they analyzed primarily short-lived student teams and because organizational virtual teams were severely underrepresented in these studies. Therefore, Purvanova and Kenda (2022) compared the impact of virtuality on team effectiveness of 73 independent samples of organizational virtual teams and 109 independent samples of non-organizational virtual teams. They found that, in organizational teams, virtuality did not show a direct positive or negative relationship with any of the team effectiveness outcomes they examined. They had analyzed the following outcomes: productive outcomes (earnings, accuracy, and process improvements), performance outcomes (including both externally rated and team member–rated team performance), social outcomes (including cohesion and team trust), and individual team member outcomes (including project/task satisfaction and relational quality). Supplemental analyses showed that these neutral relationships between team virtuality and team effectiveness in organizational teams were not moderated by virtuality operationalization (technology dependence versus geographic dispersion), industry type (information technology [IT]/telecommunication, service, and production), company type (multinational and domestic), occupation of team members (IT/engineering, research and development [R&D], and consulting/management/sales), national diversity within teams (homogeneous vs. heterogeneous), and gender diversity within teams (percent males). They also found that results from non-organizational teams were significantly more negative than results from organizational teams. However, this was not the case when studies used graduate student participants, long-term teams, continuous virtuality measures, and classroom projects instead of laboratory tasks stimulating greater participant investment.

Outcomes of Human-Autonomy Teaming

A special type of virtual teams are HATs. In their review of 76 studies on human-autonomy teaming, O’Neill and colleagues (2022) report that communication among autonomous agents and humans tended to be different than communication among humans. Performance of HATs was typically lower than performance of human–human teams because of their lower-quality communication. High reliability of autonomous agents showed consistently positive effects on outcomes such as trust, workload, and performance. However, reliability interacted with transparency. Lower agent reliability could be partially compensated by higher transparency. When humans were aware of lower agent reliability, they were more trusting and showed higher performance. However, studies on transparency on autonomous agents showed mixed effects. On the one hand, it seems that transparency can clarify the reasoning and decision making of autonomous agents. On the other hand, it may lead to less vigilance in overseeing or questioning the autonomous agents’ work.

With respect to HATs, they found that higher levels of agent autonomy and interdependence of autonomous agents and humans led to better team outcomes. Although one could assume that autonomous agents are designed to perform tasks and roles that are difficult or too difficult for humans, they did not find evidence that autonomous agents were particularly useful for teams working under conditions of high task difficulty. However, the studies they reviewed were laboratory-based and did not include field settings. Most of them used only a single human–agent dyad performing an action or execution task with a moderate level of difficulty and very limited levels of communication capabilities and partial autonomy of software agents. As studies focused on performance, workload, trust, situational awareness, team coordination, and shared mental models as dependent variables, research on team viability, development, and learning in HATs is lacking. Owing to these restrictions, caution is advised in generalizing these findings.

Practical Implications

Research findings that stronger negative effects with respect to virtual team functioning were found in short-term compared with long-term teams indicate that teams would benefit from team-building interventions to support team learning and adaptation to the specific challenges of virtual team work, such as developing task, team, temporal, and ICT shared mental models. Meta-analytic studies show that team-building interventions have stronger effects if teams are large ( Klein et al., 2009 ). This might indicate that team coordination and developing a common understanding are more challenging with increasing team size but that small teams can more easily regulate themselves.

Since the development of trust seems to take more time in virtual compared with face-to-face interactions ( Breuer et al., 2016 ), face-to-face kick-off workshops or team development interventions are recommended ( Hertel et al., 2005 ). Besides trust-building activities, documenting team interactions particularly in virtual teams is recommended, as the need for trust decreases when team interactions are documented. Study findings on HATs suggest that it is important to provide transparency regarding the capabilities and roles of software agents, particularly if systems lack reliability, but also stress human responsibility to prevent complacency ( O’Neill et al., 2022 ). Findings of communication theories suggest that this implication holds for ICTs in general.

Future Research

Study results indicate a serious method bias, as more negative effects of team virtuality are reported when short-term laboratory teams are compared with long-term organizational teams ( Purvanova & Kenda, 2022 ), and additional longitudinal studies, particularly with organizational teams, are needed. Furthermore, as team virtuality seems to be multi-dimensional, continuous measures or considering the different dimensions of team virtuality seem to be promising. It might be also worthwhile to examine non-linear effects of team virtuality and to study different forms of hybrid teams. Many studies have focused on the effects of team virtuality; therefore, more studies on mediating and moderating variables are needed to learn more about the causal mechanisms. As virtual teams are a multi-level phenomenon, consisting of individual team members and being embedded in organizations and societies, multi-level studies would be promising. Besides virtual team effectiveness, cross-level effects of virtual working conditions and team processes on individual outcomes such as perceived life-domain balance and stress could be interesting. Particularly, virtual leadership research is still needed ( Avolio et al., 2014 ). Last but not least, research on HATs is still in its beginning stages. Studies analyzing larger teams, more complex tasks, more autonomous agents, and team interaction processes and outcomes both in the laboratory and in the field are needed.

Further Reading

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• DOI: 10.1177/0149206314559946
• Corpus ID: 53004870

Virtual Teams Research

• L. Gilson , M. Maynard , +2 authors M. Hakonen
• Published 1 July 2015
• Business, Computer Science
• Journal of Management

479 Citations

The many faces of a virtual team: a review of research done on individual member input to virtual teams, virtual project teams and their effectiveness, virtual team adaptation: management perspective on individual differences (preprint), team perceived virtuality: an emergent state perspective, challenges and barriers in virtual teams: a literature review, a meta-review of global virtual team research: thematic insights and future directions, virtual team member perspectives on personal development: a sequential explanatory study, teams in a new era: some considerations and implications, interactive effects of team virtuality and work design on team functioning, understanding the dimensions of virtual teams: a study of professional students in india, 167 references, virtual teams: a review of current literature and directions for future research, research note - a model of conflict, leadership, and performance in virtual teams, influences on creativity in asynchronous virtual teams: a qualitative analysis of experimental teams, managing virtual teams: a review of current empirical research, seeing remote team members as leaders: a study of us-scandinavian teams, a meta-analysis of the consequences of virtualness on team functioning, the impact of knowledge coordination on virtual team performance over time, when success isn’t everything – case studies of two virtual teams, something(s) old and something(s) new: modeling drivers of global virtual team effectiveness, conceptualizing and measuring the virtuality of teams, related papers.

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Performance in virtual teams: towards an integrative model  †.

1. Introduction

3. literature review, 3.1. individual factors, 3.1.1. team members’ competencies, 3.1.2. motivation, 3.2. group dynamics, 3.2.1. shared mental models and norms, 3.2.2. team awareness, 3.2.3. process losses, 3.2.4. team experience.

• Team resilience can be defined as the collective capacity to deal with adverse events and rebound as strengthened and more resourceful [ 27 , 28 ]. Open communication and the quality of relationships are important factors for team-resilience development [ 2 , 29 , 30 ]. In return, it contributes to reducing the level of relational conflict [ 2 , 31 , 32 ].
• Team familiarity can lower the barriers and communication concerns created by geographic, nationality, structural, and demographic differences [ 33 ]. Moreover, professional familiarity, rather than a personal one, is salient in shaping VT’s information elaboration (i.e., exchanging, discussing, and integrating information), which has a positive effect on performance [ 34 , 35 ].

3.2.5. Knowledge Sharing

3.2.6. conflict, 3.3. context factors, 3.3.1. team virtuality and configuration, 3.3.2. task complexity and interdependence, 3.3.3. team diversity, 3.4. technology-mediated communication, 3.6. leadership, 4. research model, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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El Idrissi, A.; Fourka, M. Performance in Virtual Teams: Towards an Integrative Model. Proceedings 2022 , 82 , 73. https://doi.org/10.3390/proceedings2022082073

El Idrissi A, Fourka M. Performance in Virtual Teams: Towards an Integrative Model. Proceedings . 2022; 82(1):73. https://doi.org/10.3390/proceedings2022082073

El Idrissi, Ali, and Mohamed Fourka. 2022. "Performance in Virtual Teams: Towards an Integrative Model" Proceedings 82, no. 1: 73. https://doi.org/10.3390/proceedings2022082073

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Virtual Teams in Times of Pandemic: Factors That Influence Performance

Victor garro-abarca.

1 School of Computing, Tecnológico de Costa Rica, Cartago, Costa Rica

Pedro Palos-Sanchez

2 Department of Financial Economics and Operations Management, University of Seville, Seville, Spain

Mariano Aguayo-Camacho

Associated data.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

In the digital age, the global software development sector has been a forerunner in implementing new ways and configurations for remote teamwork using information and communication technologies on a widespread basis. Crises and technological advances have influenced each other to bring about changes in the ways of working. In the 70’s of the last century, in the middle of the so-called oil crisis, the concept of teleworking was defined using remote computer equipment to access office equipment and thus avoid moving around using traditional vehicles. Then from the 90s, with the advent of communications and the widespread use of the Internet, the first virtual work teams were implemented in software development companies that already had some of the important characteristics needed to work in this way, such as, cultural diversity, characterized tasks, geographical distribution of members, communication, interdependence of tasks, leadership, cohesion, empowerment, confidence, virtuality. This manuscript groups the main factors into different models proposed by the literature and also analyzes the results of a study conducted in the midst of the Covid-19 crisis on 317 software development teams that had to work in virtual teams (VT). The results of the quantitative methodology with structural equation modeling based on variance using the partial least squares route method are analyzed. The results of the research focus on some determinants that can directly affect the performance of the virtual team. A first determinant is communication in relation to the tasks. The second is trust in relation to leadership, empowerment and cohesion. The results of virtual teams provide information that can serve as a basis for future research lines for the implementation of virtual work strategies in post-pandemic work.

Introduction

The digital era has meant a change in the processes and routines of the business dynamics to which many organizations have had to adapt in order to compete and survive in globalized markets. The virtualization of organizational life and the digital transformation of labor relations goes hand in hand with the accelerated advance of technologies such as cloud computing, which have made it unnecessary to have tangible servers, software and hardware infrastructures in the company offices and many processes are being carried out by accessing personal equipment or terminals (computers, laptops, and mobile devices) connected to an increasingly fast Internet network. All this is possible thanks to the technology of virtualization ( Sánchez, 2017 ). Recent studies have analyzed the attitude of human resources to cloud technology and its importance in software as a service application - SaaS- ( Palos and Correia, 2017 ) and how the attitude of the worker has changed, thanks to online work training ( Palos-Sanchez, 2017 ). Thus, the digital virtualization of traditionally physical technological resources is also happening at the level of human resources, because increasingly the presence of workers in the same place is not necessary. This implies an immense challenge for the new electronic leadership of teams of collaborators who are increasingly dispersed geographically.

In the beginning, virtual teams were formed to facilitate joint creation and innovation among global or regional experts who did not have enough time to travel to fulfill the specialized tasks of the projects that required them. Today, virtual teamwork has evolved to a point where online collaboration is a way of working for national companies and more naturally for multinational or regional companies. The idea of virtual collaboration between workers, or virtual teamwork VT, consists of a team working together from different physical locations using collaborative ICTs. In the last 20 years this modality has been in constant growth due to the evolution and maturity of the digital era in terms of speed of telecommunications, the power of the computer equipment, the naturalness of adaptation to the use of ICTs in the work of digital natives (born since 1990) and digital migrants (born before 1990). However, at the beginning of the 21st century it was difficult to have faith in VTs due to the low level of maturity of virtual teams which made companies skeptical about the efficiency of this way of working. By the early 2000s, studies showed that the number of VTs that achieved their goals was not very encouraging and there was a significant failure rate. A few years later, things had not changed that much either. In 2004, there was talk of significant challenges in the implementation of virtual teams ( Piccoli et al., 2004 ). Another study ( Brett et al., 2006 ) revealed that most people thought that virtual communication was not as productive as face-to-face interaction, while half of the respondents said they were confused and overwhelmed by collaboration technology. Even so, this happened a few years ago and as technology advanced, companies matured with the use of ICT tools, so these early conclusions from the beginning of the century were not believed to be accurate anymore. A more recent study in 2009, involving 80 global software teams, indicated that well-managed virtual teams using virtual collaboration can outperform face-to-face (FtF) teams.

Additionally, a number of studies ( Jarrahi and Sawyer, 2013 ), indicate that virtual or remotely distributed team collaboration can also improve employee productivity. Therefore, an important question is: what can make a virtual team have better performance results than a face-to-face team? The answer has been provided by several studies that have summarized input factor models and their relationships with other factors grouped into socio-emotional and task-oriented processes and finally their relationships with output factors ( Powell et al., 2004 ; Gilson et al., 2015 ).

In addition to the aforementioned triggers of virtualization of organizational life and the digital transformation of processes ( Zúñiga Ramirez et al., 2016 ) and the interrelations of stakeholders as co-creators of value ( Martinez-Cañas et al., 2016 ; Ribes-Giner et al., 2017 ), it is also worth mentioning that the origin of remote work in a virtual team is originally teleworking.

Considering the above reasons and in view of finding ourselves in the midst of a rapidly evolving digital era coupled with a pandemic that has forced workers in many areas to perform remote work ( Velicia-Martin et al., 2021 ) and aligned with an effective strategy to contain and mitigate rate of spread of infection ( Brooks et al., 2020 ), this study has been undertaken in the midst of the COVID19 impact on virtual teams in the software development industry. The co-creation in virtual teamwork is a very important feature.

The main objective of this research, at a time with a pandemic and the current digital era ( Chen et al., 2020 ), is to analyze the relationship of important factors found in the literature by analyzing the performance of 317 software engineers in virtual teams. Software engineers, due to their training and experience, belong to virtual teams that include co-creation for the construction of software using agile methodologies and have recently been involved in working in virtual teams. This research is original because of the importance given to endogenous variables such as communication and trust. For this reason, the results of the survey carried out have served to understand what role different factors play in the performance of a group used to doing remote or virtual teamwork as part of their normal work. The study uses a structural equation approach with partial least squares (PLS) to evaluate the proposed performance model. The research is organized as follows. First, the Introduction explains the article based on the history of co-creation in current software development and its relationship to the study of vital equipment. Then there is a literature review, which analyzes relevant research on factors in VTs. Thirdly, methodology and justification of the hypotheses are presented. The results are then analyzed. In the Conclusions section, discussions and conclusions are made in which the practical implications of the research are given.

Literature Review

A virtual team is defined as a group of people or stakeholders working together from different locations and possibly different time zones, who are collaborating on a common project and use information and communication technologies (ICTs) intensively to co-create. It can be seen that one of the main characteristics is virtuality, which implies physical and temporal distance between members and a shared purpose ( Ebrahim et al., 2009 ).

Another essential characteristic of virtual teams, which differentiates it from traditional “face-to-face” (FtF) teams is the collaborative use of technology for work. This has been the result of the evolution of ICTs in this digital age, along with the trend toward globalization. In VTs there is naturally a geographical dispersion that entails certain cultural differences and social bonds are more difficult to achieve. All this generates a series of difficulties for communication between members and emotional relationships ( Duarte and Snyder, 2006 ; Lin et al., 2008 ; Shuffler et al., 2010 ).

Virtual teams are affected by a series of factors and phases, which have been investigated in the literature ( Abarca et al., 2020 ) and which give rise to different models for studying and relating them for performance. There are several models of VTs, from classical ones ( Martins et al., 2004 ; Powell et al., 2004 ) to a recent one ( Dulebohn and Hoch, 2017 ). Others analyze VTs at the management level ( Hertel et al., 2005 ) and others analyze them as a systemic Input-Process-Output or IPO ( Saldaña Ramos, 2010 ). This last model is based on others that studied face-to-face teams ( Hoch and Kozlowski, 2014 ) and proposes adaptations to the model when studying VT.

Research papers study the factors that influence VTs for virtual team management models and those that have a significant impact on performance are chosen and, in turn, are mentioned in the literature. As seen in Figure 1 , this study has taken into account the different phases of the IPO model and its adaptation ( Gilson et al., 2015 ) along with the factors that are organized into Inputs (related to communication and trust), Processes (task-oriented and socio-emotional) and Outputs (performance).

Reference IPO model for analyzing VTs. Source: Based on authors.

As observed in VT models, communication is studied in relation to the characteristics of the tasks that will be developed and co-created in a distributed way.

Task Features

The interaction between task type and communication and its impact on team performance has been investigated in the literature ( Montoya-Weiss et al., 2001 ; Bell et al., 2002 ; Rico and Cohen, 2005 ). Because virtual teams rely heavily on communication technologies to coordinate their work, it is necessary to examine the relationship between the nature of the task and the effectiveness of communication that impacts team performance.

Software development projects are characterized by great uncertainty in terms of requirements and risk planning and followed by technological suitability until the project is completed. Task uncertainty has been conceptualized using various dimensions of task complexity in the literature. Some of the dimensions studied are task variety and task analyzability ( Daft and Lengel, 1986 ); variability ( de Ven et al., 1976 ); uniformity ( Mohr, 1971 ); predictability ( Galbraith, 1973 ); and complexity ( Duncan, 1972 ). The proposed model of information processing by Daft and Macintosh (1981) is comprehensive and captures the nature of virtual teamwork effectively through the dimensions of task variety and task analyzability.

As seen in the VTs models, trust is considered as leadership, cohesion and team empowerment. These 3 characteristics are described in more detail below:

One definition of leadership states that it is when a person gets other people to do something ( Kort, 2008 ). Leadership is an influential relationship between leaders and followers who attempt to make changes that benefit their mutual purposes ( Kort, 2008 ).

In VTs, transformational leadership seems to also arise from personality and communication factors ( Balthazard et al., 2009 ) and can increase performance, satisfaction ( Purvanova and Bono, 2009 ) and motivation ( Andressen et al., 2012 ).

Clearly, leadership is important for VTs. In one study ( Glückler and Schrott, 2007 ) it was found that communication influenced who emerged as a leader.

Glückler and Schrott (2007) found that communication behavior influenced who emerged as a leader. Similarly, leader–member exchange ( Goh and Wasko, 2012 ), perceptions of supportive leadership ( Schepers et al., 2011 ), leadership roles ( Konradt and Hoch, 2007 ) and cross-cultural leadership ( Sarker et al., 2009 ) have received attention, and other research has studied the impact of the type of recognition a leader uses to motivate workers ( Whitford and Moss, 2009 ).

Research on VT leadership has grown rapidly, with two popular areas being leadership behavior and traits ( Gilson et al., 2015 ). Here, the work has examined inspirational aspects ( Joshi et al., 2009 ) as well as transformational and transactional leaders ( Huang et al., 2010 ; David Strang, 2011 ). In VT, transformational leadership seems to be due to personality and communication factors ( Balthazard et al., 2009 ) and can increase performance, satisfaction ( Purvanova and Bono, 2009 ) and motivation ( Andressen et al., 2012 ).

Several studies have examined the interaction between leadership and virtuality, finding that team members are more satisfied with their team and leader and perceive that their leader is better able to decode messages when the leader is geographically distant from the team ( Henderson, 2008 ). Hoch and Kozlowski (2014) found that virtuality dampened the relationship between hierarchical leadership and performance while improving the relationship between structural supports and performance.

Clearly, leadership within VTs is important. As such, leaders can play a central role in how a VT works, particularly because they influence how a team deals with obstacles and how the team ultimately adapts to such challenges. This can be seen in articles on team adaptation research ( Baard et al., 2014 ).

Other research suggests that classic leadership styles are appropriate for a virtual team:

Democratic ( McBer and Company, 1980 ) and referee leadership styles ( Rashid and Dar, 1994 ) have some characteristics that are very suitable for a virtual team. One negative factor could be that many meetings are needed to reach consensus. In a virtual team, it is difficult and time-consuming to hold meetings for each decision.

Operational leadership ( McBer and Company, 1980 ) may be a good option because this leadership style gives team members clear roles and tasks. In addition, the leader makes the processes and structures very clear, so lack of communication will be reduced. A negative feature of this style of leadership for virtual teams might be that the contribution of the team members, and their responsibilities, might be a little less than the team members want.

Coaching leadership ( McBer and Company, 1980 ) fits virtual teams very well because it gives a lot of freedom to the team members, which means that they are also responsible for their work and results. Team members can set their own goals and therefore also progress personally while working in the virtual team. This leadership style, however, also has some difficulties. The processes, structures and roles of the team may not always be very clear because the leader allows team members to establish and use their own. Therefore, the success of the virtual team might suffer a little.

According to Salisbury et al. (2006) research into classical teams ( Lott and Lott, 1965 ; Hogg, 1987 ) suggest that the physical distance between members can be translated into a psychological distance between them. Following this line of reasoning ( Salisbury et al., 2006 ) the physical dispersion of the virtual team could inhibit cohesion. In addition, virtual team members may have different ideas about what cohesion is. In other words, the idea of cohesion, which is the communication between group members, is affected by the medium used to communicate. This is especially true given the ease with which users can exchange non-task related information in some environments. Clearly, the differences in communication patterns between virtual and onsite teams suggest that measures (such as PCS) which are used in one context cannot be directly employed in another without reevaluating them ( Boudreau et al., 2001 ).

Studies about group behavior ( Hogg and Tindale, 2001 ) consistently report that, in working groups, the members’ ability to get along with each other is critical for well-being and task performance. The importance of developing such intra-group cohesion has been shown to be especially relevant in cases where members don not know each other, such as in newly formed groups or when members are assigned to new project teams ( Griffin, 1997 ). The Symbolic Convergence Theory (SCT) proposed by Bormann (1983 , 1996) and tested by Bormann et al. (1994 , 1997) provides a rich theoretical framework for understanding group cohesion in traditional and technology-based teams.

One type of group cohesion is task cohesion and occurs when members stay together because they are strongly involved with the group’s tasks. Task cohesion will be greater if members identify with the group’s tasks and find them intrinsically rewarding and valuable.

Group cohesion for virtual teams with members working at different geographic locations, for different organizations, and even in different sectors of the economy, need effective communication and close coordination to achieve goals ( Powell et al., 2004 ).

The positive relationship between cohesion and trust in working teams has been confirmed in many investigations ( Evans and Dion, 1991 ; Simons and Peterson, 2000 ; Baltes et al., 2002 ; Powell et al., 2004 ; Spector, 2006 ; Lu, 2015 ).

Empowerment

Empowerment is favorable acknowledgment by the team leader and allows team members to participate in decision making. Empowerment makes the team member trust the leader, and when the leader asks for opinions and comments, he or she processes them and makes decisions based on the suggestions.

Some past studies ( Kirkman et al., 2004 ) indicate that teams can be empowered in four different ways, (a) power, which is the collective belief that a team can be effective, (b) significance, which is the extent to which team members care about their tasks, (c) autonomy, in which team members have freedom to make decisions; and (d) impact, the degree to which team members feel that their tasks make important contributions.

The impact of team empowerment on the performance of EVTs in 10 telecommunications companies in Islamabad was studied by Gondal and Khan (2008) . That study found that there is a positive relationship between team empowerment and team performance in telecommunications teams. Team performance includes the variables of cooperation, coordination, trust, cohesion, effort, mutual support, team conflict, job satisfaction and effectiveness in terms of quality.

Kirkman et al. (2004) also studied 35 sales and service teams at a high-tech firm and investigated the impact of team empowerment on team performance and the intermediary role of face-to-face interaction. They found that team empowerment is positively related to both constructs of virtual team performance, which are process improvement and customer satisfaction.

As indicated ( Kirkman et al., 2004 ) empowerment in a virtual team can be a substitute for the leadership tasks of a single team leader ( Kerr and Jermier, 1978 ). The behavior of the team members due to the leader’s empowerment is directly and positively related to trust. It is considered a confidence-building attribute. For empowerment, commitment is only reached when the team has a shared vision and honest and regular communication with the leader.

Models usually study the processes of tasks by investigating communication and the social-emotional processes of trust. The degree of virtuality and the interrelationship of tasks are also considered important for performance.

Communication

In mixed teams, where some members are at the same physical location and others are not, communication problems can also occur. Team members at the same physical place often communicate in a deeper way than with the distant members and this ends up causing friction between them and, therefore, damages the performance of the team ( Powell et al., 2004 ).

Communication, coordination and knowledge sharing are essential elements of action processes to predict the efficiency and effectiveness of the team ( Kock and Lynn, 2012 ).

Another study ( Peñarroja et al., 2013 ) found that as virtuality increased, team coordination declined, but this relationship was partially mediated by levels of trust.

Early research on VTs proposed that initial FtF meetings should help encourage performance ( Geber, 1995 ). Han et al. (2011) extended this line of reasoning to creativity and compared modes of initial communication to assess their impact.

Understanding how, why, and under what conditions trust develops remains a popular research topic. In part, the importance of trust can be attributed to results that suggest it positively affects the success of VTs ( Furumo, 2009 ).

For VTs, trust is influenced by communication behavior, timely responses, open communication, and feedback ( Henttonen and Blomqvist, 2005 ).

More recent findings suggest that rapid trust is likely to be established with early communication and a positive tone ( Coppola et al., 2004 ) and may influence performance by improving member confidence and subsequent trust ( Crisp and Jarvenpaa, 2013 ).

Other research has studied the impact of global VTs on trust development ( Lowry et al., 2010 ). Culturally heterogeneous teams (China and the United States) and homogeneous teams were compared and no significant differences were found in the trust between FtF teams and VTs ( Lowry et al., 2010 ).

Furthermore, in a longitudinal study of global VTs, Goh and Wasko (2012) found that when everyone’s actions were visible, trust was not a key factor in resource allocation.

Finally, in globally distributed teams, trust mitigated the negative effects of member diversity on performance ( Garrison et al., 2010 ).

Finally, aspects such as performance, quality of the product or service obtained and member satisfaction are relevant for the results. Of course, performance is the essential variable and is the usual interest of research into virtual teams.

Performance

Overall, research suggests that working in VTs can have a positive impact on effectiveness ( Kock and Lynn, 2012 ; Maynard et al., 2012 ), while others provide evidence suggesting that virtual working affects effectiveness negatively ( Cramton and Webber, 2005 ; Schweitzer and Duxbury, 2010 ).

A positive trend appears to be that work in this area is beginning to take advantage of ratings from outside the team ( Andressen et al., 2012 ; Cummings and Haas, 2012 ), as well as objective measures of team performance ( Rico and Cohen, 2005 ; Rapp et al., 2010 ).

In considering the elements of effectiveness, several researchers have examined the quality of the project ( Altschuller and Benbunan-Fich, 2010 ). This makes sense, since VTs are often used for special projects. In addition, the quality of the decisions made and the time taken to reach a decision have been studied and the findings are often that VTs need more time to make decisions ( Pridmore and Phillips-Wren, 2011 ).

Other studies find that VTs that set goals early in their life cycle showed greater cohesion and performance ( Brahm and Kunze, 2012 ).

Other work in this area also suggests that team motivation and performance can be improved by using mixed incentive rewards ( Bryant et al., 2009 ).

One study ( Kirkman et al., 2013 ) considered the impact of national diversity on performance and found a curvilinear (U-shaped) relationship moderated by both media richness and psychological safety.

Materials and Methods

The present study was carried out to understand the factors which influence the performance of VTs in a professional team that is used to using “agile” methodologies and virtual working.

A quantitative causal study using partial least squares (PLS) was performed using an online questionnaire, with a sample of 317 participants (Software Engineers).

Questionnaire and Measurement Scales

A quantitative research divided into the following blocks was designed and then carried out and the results were used to test the hypotheses that constitute the theoretical model. The details are shown in Table 1 .

Variables of the proposed model.

Proposed Model

The proposed model that incorporated the hypothetical relationships is illustrated in Figure 2 .

Proposed model.

Research Hypotheses

The research hypotheses for the investigation of the factors that influence the performance of virtual teams are presented below.

Considerations of the Research Approach in the Hypotheses

Due to the quantitative approach chosen and by virtue of the delimiting nature of quantitative research, the hypotheses constitute the behavior that the variables or constructs are expected to show in the software development VT environment. Figure 2 shows the initial model. The hypotheses that are to be tested in this study are presented below:

• H1: The characteristics of the tasks have a direct and positive influence on the communication of the virtual team members.
• H2: The level of leadership of the members of the virtual team has a direct and positive influence on trust.
• H3: The level of cohesion of the members of the virtual team has a direct and positive influence on trust.
• H4: The level of empowerment of the members of the virtual team has a direct and positive influence on trust.
• H5: Communication between virtual workers has a direct and positive influence on the confidence of the virtual team.
• H6: Trust among virtual workers has a direct and positive influence on the performance of the virtual team.
• H7: The level of communication between virtual workers has a direct and positive influence on the performance of the virtual team.

Hypothesis Research Scope Considerations

The correlational scope used to find the relationships between variables that give an answer to a problem means that without proving these relationships there could be a causal link between the variables. Figure 2 shows the constructs of the hypotheses in the study model.

Additionally, it is important to reiterate, that the VT performance construct is based on the relationships with the aggregate constructs Communication (h9) and Trust (h10) which in turn are expected to have a strong relationship between them and this will be tested in the research (h7 and h8). Then, the latent variable called communication has the constructs of cultural diversity (h1), the characteristics of the tasks (h2), as well as the distribution index (h3). Finally, the variables leadership (h4), cohesion (h5), and empowerment (h6) are used to find the latent variable trust.

The model used for the research hypotheses, its variables and its relationships are described in the literature review section.

Sampling and Data Collection

1,200 software engineers with experience in programming with Agile methodology (which involves co-creation and collaboration in virtual teams) and who had graduated in the last 10 years, were directly invited to take part in the survey. 317 responses were collected.

The study was designed based on robust studies previously applied to telework and virtual teams in globally distributed teams for 20 years and after a robust literature review on the most relevant factors affecting the performance of these teams.

The study was applied at a privileged moment 3 months after the official declaration of the Covid pandemic19 by The World Health Organization.

The population taken into account for this study is considered stable because they were graduates of accredited engineering degrees from universities recognized in Costa Rica for their training in software development over the past 20 years and related colleagues.

Parallel to this study, a control study was conducted on another more heterogeneous population of professionals who in many cases had to start from scratch in the form of teleworking or virtual teams. This helped to understand and further refine the proposed model.

Demographic Details

As can be seen in Table 2 , the results found for the demographic features of the 317 members of virtual teams that use agile methodologies for the development of their projects are tabulated.

Demographic details.

For gender, it is normal that in Software Engineering (SE) there is a higher proportion of men (81%) than women (19%). For age, it should be noted that 65% of those who responded to the questionnaire about virtual teams of SE were digital natives (born after the 1990s).

For the time spent working in VTs, almost 90% of the young members of SE VTs had joined in the last 5 years, which is consistent with handling agile methodologies and virtual teams in this profession.

The proportion of leaders is approximately 30% of the group and members 70%. In the SE VTs it was notable that 58% of the members have also been project leaders before, due to the dynamics of the Agile methodology and value co-creation. The diversity of membership in organizations shows that the members from SE VTs were 25% of the sample group and the members of VTs from other professions (OP) were 5% due to their recent incorporation into this way of working.

The members of SE VTs (68%) were very interested in continuing working in VTs in a new post-Covid19 normality.

Important Findings

It is clear that the objective of the work is to analyze the determinants of performance in virtual teams in a time of pandemic, where conditions forced the vast majority of workers to develop their work within their homes remotely, forming virtual teams in which they already participated or had to organize in this way. With this objective, a survey has been conducted among software engineers and they have specified a structural equation model to analyze the relationship between different inputs and processes in the output. The results obtained show the relevance of communication and confidence in the performance of virtual teams. But before reviewing the complete model it is important to mention some important findings:

• – The participants in this study were professionals in the area of computer science, dedicated to the development of software. Mainly digital natives with experience in VTs, people with ages between 18 and 29 years (64.98%) and digital migrants between 30 and 39 years (18.93%) with high mastery of information and communication technologies ICTs. In general, they consider that virtual teamwork is an excellent way to develop their work in the world of technology. It is part of their profession. In the worst case, some engineers maintain a neutral stance toward the issue of virtual teamwork. Under normal conditions they have worked in virtual mixed mode and face to face, so under 100% pandemic conditions, they really didn’t have much of an adjustment problem, because they were already doing it before. Even when asked about the future, a high number (68.45%) see themselves working in virtual teams and 28.71% in mixed mode.
• – The professionals interviewed in many cases have indicated that communication in virtual teams is a factor that must be improved in frequency and quality because they feel that the initial instructions are not enough. Others take communication as a natural factor, regardless of whether the communication is virtual or face to face. Finally others indicate that communication in the virtual team is better with the good use of collaborative tools.
• – Trust is a very important factor in the study, because it allows employees to perform their tasks at a distance in a better way, as long as their tasks are measured by objectives. Too many controls throughout the work process make the virtual collaborator feel watched and that he is being evaluated negatively.
• – Regarding the geographical distribution, software engineers agree with professionals from other areas in that it saves them time and money and due to the intensive and natural use of ICT in their profession, the physical distance was not relevant to achieve the objectives.
• – Regarding the cultural diversity in this study, being regional, the interviewees gave positive answers because the cultural differences did not influence their performance in the software development projects that have in common in a standardized way the computational language and the technological architectures.
• – About the distribution of tasks, to be developed projects with agile methodologies, the specifications of functional and technical requirements are very clear from the beginning and also are clarified or refined in time with the coordination, co-creation and collaborative work, so engineers have clear what their tasks are throughout the process. As for the Interdependence of tasks there was no significant finding at the level of software development operations. It is possible that this is due to the fact that software projects are structured at the level of by-products and tasks in an orderly manner.
• – By using agile methodologies to develop work with virtual teams and distributing tasks among members early on, empowering each member individually and in relation to others has been vital in software projects. Depending on the level of experience and individual skills, empowerment is increasingly important in virtuality.
• – Leadership is a fundamental issue, which directly influences the confidence of virtual collaborators. In this study the members of the virtual teams gave it a moderate importance because of the work methodology and the mixed experience: virtual and face to face, the works are done in a collaborative and very horizontal way. Additionally, 58.04% indicated that they had already led some software development in this modality in the past.
• – The virtual team software development has made the collaborators work longer interacting through the ICTs, fighting to achieve common objectives. This has made that the cohesion between them has increased at work level.

Sample Frame

A random database of 1,000 software engineers graduated in the last 20 years from accredited software engineering or systems engineering careers at universities in Costa Rica, a country with a tradition and recognition of many years of software development for the region of Central and North America (mainly United States), was taken into account.

The survey was applied from May to July 2020, in the midst of the Covid19 pandemic, using an email invitation for respondents to fill out an electronic survey instrument using the Google Forms platform with 65 items.

Limitations

There are many factors previously studied that influence in one way or another the performance of VTs, but at the level of the proposed model they cannot all be included because they have shown that their influence has not been very strong or because the type of population that was chosen for this specific study was not relevant. For example, a limitation of this study is that the dimension of rewards was not considered, since in recent similar studies they have not shown significant relationships ( Tan et al., 2019 ).

A second limitation that could be considered, is related to the fact that, the respondents belong to different institutional environments, regularly projects of 5–10 members, in medium sized software development companies. In this sense, it is common that they use agile methodology as the project organization standard, which compensates for the differences in size of the parent organization, type of products developed, the member’s country of origin and the country of origin of the final client.

The cultural diversity that has been extensively studied in virtual teams, in this study was included in the survey but its results did not show a significant influence because the software development projects were usually regional and associated with the same continent and time zones with few differences.

Analysis of Results

Results for the measurement model.

The measurement model was tested for internal reliability, convergent validity and discriminant validity. The internal reliability was evaluated using Cronbach’s alpha which needs a value of at least 0.70 for acceptable internal consistency ( Hair et al., 2013 ). Causality was analyzed using indicator loadings. Composite reliability was also used to investigate causality ( Werts et al., 1974 ). All the constructs had internal consistency as all the values for Cronbach’s alpha were higher than 0.7 ( Fornell and Larcker, 1981 ; Bagozzi and Yi, 1988 ; Hair et al., 2011 ). Fornell and Larcker (1981) used the Average Variance Extracted (AVE) to assess convergent validity, and stated that an acceptable value for this factor is AVE ≥ 0.50.

Table 3 shows the element loads, Cronbach’s alpha and AVE which were found for the constructs. Values for Cronbach’s alpha ranged from 0.914 to 0.709, which is higher than the recommended level of 0.70 and therefore indicates strong internal reliability for the constructs. The composite reliability ranged between 0.946 and 0.837 and the AVE ranged between 0.632 and 0.853, which are higher than the recommended levels. The conditions for convergent validity were therefore met. The discriminant validity was calculated with the square root of the AVE and the cross-loading matrix. For satisfactory discriminant validity, the square root of the AVE of a construct should be greater than the correlation with other constructs ( Fornell and Larcker, 1981 ).

Reliability, validity of the constructs, Fornell–Larcker criterion and HTMT.

These researchers carried out simulation studies to demonstrate that a lack of discriminant validity is better detected by means of another technique called the heterotrait-monotrait ratio (HTMT), which they had discovered earlier. All the HTMT ratios for each pair of factors was <0.90.

Results for the Structural Models

The structural model was built from the different relationships between the constructs. The hypotheses for the study were tested by analyzing the relationships between the different constructs in the model to see if they were supported ( Chin and Newsted, 1999 ; Reinartz et al., 2009 ).

The variance is found from the values for the reflective indicators of the constructs ( Barclay et al., 1995 ; Chin, 2010 ). This was found numerically by calculating the values of R 2 , which is a measure of the amount of variance for the construct in the model. The bootstrap method was used to test the hypotheses. The detailed results (path coefficient, β, and t -statistic) are summarized in Table 4 and Figure 3 .

Results of hypothesis: path coefficients and statistical significance.

Final model. *** p < 0.001 [ t (0.001; 499) = 3.106644601].

The measurements for approximate adjustments of the model ( Henseler et al., 2016 ; Henseler, 2017 ) are given by the Standardized Root Mean Square Residual (SRMR) value ( Hu and Bentler, 1998 ) which measures the difference between the observed correlation matrix and the implied correlation matrix of the model. SRMR shows the average magnitude of these differences.

A low value of SRMR means that the fit is better. In our case SRMR = 0.055, which was within the recommendations for a model with a good fit. A good fit is considered to be shown with a value of SRMR < 0.08 ( Hu and Bentler, 1998 ).

The following conclusions were made from the values for R 2 (see Table 5 and Figure 3 ) found in the research by Chin (1998) and show that 0.67 = “Substantial,” 0.33 = “Moderate,” and 0.19 = “Weak.” The result obtained for the main dependent variable of the model, Performance (PER) R 2 = 48.4% was moderate and the rest of constructs, Trust R 2 = 74.2% and Communication (COM) R 2 = 33.3%.

R 2 results.

This value shows that this model is “substantially” applicable to the performance of virtual teams. Please note that the variables that are not endogenous do not have a value for R 2 .

The results obtained for the proposed model have found that the performance of virtual teams is moderately justified by the determinants as R 2 = 48.4%. However, the value obtained for Trust ( R 2 = 74.2%) should be noted as it means that the variance of this construct explains to a high percentage, aspects such as the confidence of the virtual team. This is essential to improve the co-creation of software development teams.

This study confirmed that the most significant variable for the performance of the EVT is Trust (H6), since this variable has the strongest influence on the dependent variable Performance. It also has a very high predictive capacity as the determination coefficient is high (β = 0.684; t = 14.281).

These results coincide with other recent findings that confirm that Trust can influence performance by improving member confidence and the subsequent trust ( Crisp and Jarvenpaa, 2013 ). So when everyone’s actions are visible, trust was not a key factor in resource allocation ( Goh and Wasko, 2012 ).

The next most important variable in the model is Task features (H1). Virtual teams rely heavily on communication technologies to coordinate their work, so the relationship between the nature of the task and the effectiveness of communication was studied in order to find its subsequent impact on team performance. Therefore, one of the determinants was the characteristics of the tasks and the positive influence on the communication of the members of the virtual team. The result was positive with a confidence level of 99.9%. Therefore, H1 was supported (β = 0.577; t = 13.842). These results amply confirm that great uncertainty about the requirements and the risk planning, followed by the technological suitability of the projects, are key to communication.

Our study also confirmed that the level of empowerment of the members of the virtual teams was also found to have a significant effect on Trust (H4). This result showed that Empowerment positively promotes and increases the confidence of a virtual team (β = 0.348; t = 7.086).

These results coincide with previous work ( Gondal and Khan, 2008 ) that measured the impact of team empowerment on VT performance and demonstrated that there is a positive relationship between team empowerment and team performance in virtual teams. Our findings go further and state that this is achieved with Trust. As with other studies ( Kirkman et al., 2004 ), empowerment in a virtual team can work as an alternative to leadership. Thus, the activities that are normally done by a team leader can be carried out by the members ( Kerr and Jermier, 1978 ) by contributing with co-creation. This behavior of the team members because of the empowerment of the team members by the leader has a direct and positive relationship with trust. It is considered a confidence-building attribute. In empowerment, commitment is only reached when the team has a shared vision and honest and regular communication with the leader.

The relationship with the next highest confidence level for trust in the virtual teams was H3: the level of cohesion of the members of the virtual teams (β = 0.366; t = 6.725). This finding shows that the ability of the members of a virtual team to get along with each other is critical to the well-being of the group and task performance. These findings are consistent with previous work ( Evans and Dion, 1991 ; Simons and Peterson, 2000 ; Baltes et al., 2002 ; Powell et al., 2004 ; Spector, 2006 ; Lu, 2015 ).

Therefore, it will be very important for software development companies to implement intragroup cohesion measures. These findings are consistent with other work ( Griffin, 1997 ). Similarly, managers could implement economic incentives that support their software developers to be strongly involved with the group’s tasks. Task cohesion will be greater if members identify with the group’s tasks and find them intrinsically rewarding and valuable.

In the current context with the Covid-19 pandemic, this cohesion has been highly questioned. Let’s not forget that the isolation measures decreed by many governments have made it difficult to deal with aspects such as different geographical locations, belonging to different organizations, and different sectors of the economy. This has made effective communication and close coordination difficult. However, the results reaffirm the theories already shown ( Powell et al., 2004 ).

One of the factors is the level of leadership of the members of the virtual teams (H2). The results showed that this had a direct and positive influence on Trust (β = 0.138; t = 3.209). Clearly, leadership in VTs is important. The results obtained coincide with the study by Baard et al. (2014) and show that the role of leaders is important for working in a VT, especially because leaders influence the way a team faces obstacles and the way the team ultimately adapts to such challenges, which is very important for the confidence generated for the future.

Therefore, the leader of a virtual team must use a style that generates Trust as a mediating factor in the indirect effect that this has on Performance.

The Communication between virtual workers has a direct and positive influence on the confidence of the virtual team and was supported (β = 0.160; t = 3.741) with a confidence level of 99.9%. Our study does support this hypothesis and agrees with Peñarroja et al. (2013) , who found that as virtuality increased, team coordination declined, but this relationship was partially mediated by levels of Trust. In addition, as can be seen in the results, it is the least strongly supported hypothesis.

H7, the level of communication between virtual workers has a direct and positive influence on the performance of the virtual team, was not supported (β = 0.019; t = 0.353). This outcome appears to be conditioned by the very high levels of virtuality that have been reached during the containment measures decreed by governments at the start of the Covid-19 pandemic and, as stated above, clearly demonstrate that communication influences trust only through trust.

This result reaffirms the role of trust-building in achieving the highest performance of the virtual team and allows us to conclude that the confidence of all members in the virtual team is key to success in software development.

The proposed model based on the IPO adaptation ( Gilson et al., 2015 ) has been largely validated using a PLS-SEM analysis. Therefore, software companies can use it as a theoretical framework when preparing their human resources and Virtual Teams management policies.

The important role of Trust as a basis for most of the variables of the model shows that it should be considered as one of the most important and relevant variables, especially because of the increase in virtualization and teleworking during the Covid-19 pandemic. Companies must give greater importance to Trust and take into account that all measures which strengthen leadership, communication, cohesion or the configuration of task characteristics must be designed considering the trust generated. It is interesting to note that economic incentives can help with group cohesion and policies improve empowerment. One such incentive could be skills training for group members. These measures may become more important than leadership in the coming years, given the results found during the pandemic.

Finally, this study was completed with software developers who use agile methodologies and who have good IT skills. The results, therefore, show that the increased virtuality brought about by the pandemic can be an opportunity to innovate in communication to influence performance.

Data Availability Statement

Author contributions.

VG-A undertook the research, collected the data, and prepared the initial manuscript. PP-S completed, revised, and finalized the manuscript, and participated in the preparation of the manuscript. MA-C provided the intellectual input and analyzed the data. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Conflict in virtual teams: a bibliometric analysis, systematic review, and research agenda

International Journal of Conflict Management

ISSN : 1044-4068

Article publication date: 6 June 2022

Issue publication date: 6 January 2023

The purpose of this study is to map the intellectual structure of the research concerning conflict and conflict management in virtual teams (VT), to contribute to the further integration of knowledge among different streams of research and to develop an interpretative framework to stimulate future research.

Design/methodology/approach

A data set of 107 relevant papers on the topic was retrieved using the Web of Science Core Collection database covering a period ranging from 2001 to 2019. A comparative bibliometric analysis consisting of the integration of results from the citation, co-citation and bibliographic coupling was performed to identify the most influential papers. The systematic literature review complemented the bibliometric results by clustering the most influential papers.

The results revealed different intellectual structures across several types of analyses. Despite such differences, 41 papers resulted as the most impactful and provided evidence of the emergence of five thematic clusters: trust, performance, cultural diversity, knowledge management and team management.

Research limitations/implications

Based on the bibliometric analyses an interpretative research agenda has been developed that unveils the main future research avenues. The paper also offers important theoretical contributions by systematizing knowledge on conflict in identifying VTs. Managerial contributions in the form of the identification of best practices are also developed to guide conflict management in VTs.

Originality/value

The uniqueness of this paper is related to its effort in studying, mapping and systematizing the knowledge concerning the topic of handling conflicts in VTs. Considering the current contingencies, this research is particularly timely.

• Virtual teams
• Conflict management
• Bibliometric analysis
• Remote working

Caputo, A. , Kargina, M. and Pellegrini, M.M. (2023), "Conflict in virtual teams: a bibliometric analysis, systematic review, and research agenda", International Journal of Conflict Management , Vol. 34 No. 1, pp. 1-31. https://doi.org/10.1108/IJCMA-07-2021-0117

Emerald Publishing Limited

Copyright © 2022, Andrea Caputo, Mariya Kargina and Massimiliano Matteo Pellegrini.

Published by Emerald Publishing Limited. This is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

Handling conflicts properly in teams is crucial for possible success ( Caputo et al. , 2019 ). Due to the specific contingencies experienced by virtual teams (VTs), this aspect becomes even more prominent ( Gilson et al. , 2015 ). The Covid-19 pandemic forced many organizations to implement remote working, often in an abrupt and fast way, indicating a particularly favorable historic momentum to systematize previous knowledge on the topic and to offer ways forward. With such a purpose in mind, this paper aims to provide an overview of the evolution of the literature regarding conflict and conflict management in the context of VTs over the past two decades. For this study, we broadly define conflict as the situation where parties within a VT perceive that their goals or interests are incompatible or in opposition ( Ayoko and Konrad, 2012 ); whereas we consider conflict management to refer to the understanding of conflict as a whole, its antecedents, the process, the styles and strategies of handling conflicts and associated behaviors in the context of VT ( Caputo et al. , 2018a ). Even in the context and dynamics of the virtuality of VTs, we concur with Caputo et al. (2018a , 2018b , p. 11) that:

The main objective of conflict management is not to eliminate conflict, but to find different ways to manage it properly by controlling the dysfunctional elements of the conflict while facilitating its productive aspects.

The Covid-19 pandemic has accelerated the already rapid development of technologies in information and communication, further reducing the distances and increasing remote work interactions ( Garro-Abarca et al. , 2021 ). The hyper-globalization processes of the past decades have led, already before the pandemic, to the growing importance of VTs in today’s organizations ( Gibson et al. , 2014 ). VTs can be considered as groups of geographically dispersed co-workers who work interdependently, share common objectives, practices and procedures using technology to communicate and collaborate across time and space ( DeSanctis and Monge, 1999 ). These teams may come from different cultures, yet they operate in the same organizational cultural framework, can bring together a variety of knowledge and experience and deal with a high degree of technologically mediated interactions ( Batarseh et al. , 2017 ). These factors contribute to making today’s organizations more diverse and possibly more conflictual.

Previous reviews and conceptual work have touched on the issues related to conflict and conflict management in the context of VTs. In particular, Schiller and Mandviwalla (2007) highlighted the issues related to conflict management in VT in an early theoretical piece that looked at the use of theories in VT research. More recently, Gilson et al. (2015) presented a seminal overview of the research in VTs that unveiled 10 themes and 10 opportunities for future research. According to the authors, conflict management was mostly studied as a mediator in a unidimensional relation, resulting in the suggestion that conflict is more likely to happen in VTs and it negatively affects team dynamics, processes and outcomes. A similar suggestion is made by Jimenez et al. (2017) , in reviewing the works about global VTs, and Raghuram et al. (2019) , reviewing studies about virtual work, who highlighted how conflicts emerge mostly from cultural and language differences affecting team dynamics. The fragmentation of empirical literature about conflict in VTs and the limited conceptual attention given to the topic calls for an investigation and systematization of the literature about conflict and conflict management in VTs as timely and necessary to support both research and practice to navigate the uncertainties of today’s world.

Shedding light on the evolution of the study of conflicts and their associated management in VTs, a bibliometric analysis of 107 relevant articles published in peer-reviewed scientific journals has been performed to first identify the most influential studies and second, to systematize the academic knowledge by unveiling the existence of five thematic clusters: trust, performance, cultural diversity, knowledge management and team management. In particular, an innovative approach has been adopted by comparing results from alternative, complementary bibliometric tools, i.e. citations, normalized citations and bibliographic coupling, to identify the most influential articles in the field ( Caputo et al. , 2021 ).

This study provides several contributions theoretically, methodologically and practically. First, it contributes to strengthening the integration and systematization of the two bodies of literature in conflict management and VTs. Second, it provides a rigorous and systematic identification of the most influential papers in these fields and identifies thematic areas to bring forward the research. Third, it contributes to bibliometric and reviews studies by advancing the use of comparative bibliometric approaches. Finally, the paper interprets in an integrative framework the current knowledge on the field comprising nonlinear and recursive loops between its elements and, thanks to that, elaborates future research avenues.

The paper is organized into five sections, including this introduction, as follows. Section 2 describes the protocol adopted for selecting the paper and the analyses performed. Section 3 presents the results of the analyses and determines the most impactful papers. Section 4 uses the most impactful papers to propose a framework aimed at suggesting an agenda for future research. Section 5 summarizes the contributions of the paper and its limitations.

This paper aims to provide a comprehensive yet succinct and timely knowledge map of the studies investigating conflict management in VTs. Such a knowledge map is purposed to provide both scholars and practitioners with an overview of what we know i.e. best practices and main findings, and what we still do not know i.e. future research directions about managing conflict in virtual workplaces. The Covid-19 pandemic that resulted in large part of the office workforce working remotely is disrupting social relationships in the workplace. A review of conflict management in VTs is therefore necessary and needs to be carried out in a timely fashion to serve its purpose.

To achieve these objectives, we have built upon best practices in systematic literature review and bibliometric studies and complemented the two methodologies to fulfill simultaneously the breadth and depth of the analysis. The simultaneous use of these two complementary methods, albeit recent, is not entirely new as it has been validated in several studies ( Caputo et al. , 2021 ; Caputo et al. , 2018b ; Dabić et al. , 2020 ). It allows researchers to investigate a topic in depth through the systematic review while maintaining a wider picture of the evolution of knowledge through bibliometric analysis. In this study, we have also included a methodological innovation in the complementary use of alternative bibliometric analyses to identify the most influential papers in the field.

2.1 Sampling protocol

Consistent with the systematic review method ( Thorpe et al. , 2005 ; Tranfield et al. , 2003 ), a panel of experts was formed to define the field of research, choose the keywords, the database and the set of inclusion and exclusion criteria. The panel of experts consisted of two professors, one an expert in strategy, negotiation and conflict management and the other in organizational studies and team working, together with a PhD student specifically focused on the organizational dynamics of dispersed teams. A step-by-step process was followed as outlined in this section.

Step 1 . The database Web of Science (WoS) Core Collection® (research areas “Business Economics” and “Psychology”) was chosen after several alternative searches in Scopus and EBSCO because it retrieved a sample of high-quality articles representative of the best conflict in VTs research published to date. The choice of WoS Core Collection® is also supported and validated as appropriate for the field of inquiry by recent bibliometric studies in conflict management ( Caputo et al. , 2019 ).

Step 2 . A wide search string based on multiple levels of keywords was used ( Caputo, 2013 ) to ensure the capture of the most relevant papers on the topic. The first level included the keyword “Conflict”. The second level included the keywords about the remote/virtual nature of the investigated relationships: “smart OR virtual OR distributed OR distant OR remote”. The third level included keywords related to the organizational aspect of the teams, including “team OR group OR workplace OR workspace”. The search was run with Boolean operators (AND and OR) via the TS command, which searches among Title, Abstract, Author Keywords and Keywords Plus®. Consistent with best practices in bibliometric research and to ensure the comparability among the indicators, the year 2020 was excluded ( Caputo et al. , 2019 ). The search was carried out among peer-reviewed articles written in the English language and resulted in the first sample of 397 papers.

Step 3 . Due to the wideness of the search string, we proceeded to the manual “cleaning” of the data set by reading all the titles and abstracts of the selected papers to eliminate those that were not relevant to our search. When it was not possible to assess the relevance of the abstract, we obtained a digital copy of the full text of the paper. Excluded papers fall into two main categories: a large number of papers do not investigate conflict at all ( Ebrahim, 2015 ; Presbitero and Toledano, 2018 ), although the word “conflict” is presented in the search items. This situation mainly occurs because many papers had a declaration of conflict of interest that was caught by the search; others were eliminated because they simply mentioned “conflicting results” in the abstract or where conflict was just mentioned incidentally; a smaller portion of papers investigated conflict but not in a virtual environment ( Sheehan et al. , 2016 ). Following these criteria, two-hundred-ninety-three papers were eliminated because they were not relevant.

2.2 Analyses

The final data set of 107 papers was used as a basis for both the bibliometric analysis and a qualitative systematic literature review to develop a comprehensive map of the knowledge of the field.

Bibliometrics is a subset of scientometrics and applies statistical methods to the study of scientific activity in a scientific community ( Zupic and Čater, 2015 ). For our research, we followed the perspective known as positive bibliometrics ( Todeschini and Baccini, 2016 ). This is because we aim to describe and explain phenomena in science via the analysis of its scientific communication. In this view, bibliometric indicators represent phenomena or proxies of phenomena. For example, the citations received by an article that expresses a concept are a proxy of the diffusion and impact of said concept in the scientific community. Examples of positive bibliometrics are citation analysis, co-citation analysis, citation networks and productivity analysis.

Complementary bibliometric analyses were instrumental to identify the sample of the most influential papers to review. Prior studies argue for the use of more than one indicator ( Caputo et al. , 2019 ; Dabić et al. , 2020 ) as an effective way to limit the intrinsic bias that every indicator has.

First, we undertook a performance analysis based on indicators of activity. These indicators provide data about the volume and impact of research during a given timeframe via word frequency analysis, citation analysis and counting publications by the unit of analysis (e.g. authorship, country, affiliation, etc.).

Second, we built a science map based on indicators that provide spatial representations of how different scientific elements are related to one another to picture the structural and dynamic organization of knowledge about conflict management in VTs. We combined results from co-citation analysis and bibliographic coupling to identify the most influential papers, authors and journals and the co-occurrence of keywords analysis to identify the thematic structure of the field. Co-citation analysis “constructs measures of similarity between articles, authors or journals by using the frequency with which two units are cited together, i.e. co-citation counts” ( Caputo et al. , 2019 ). Therefore, co-citation analysis is powerful in showing a picture from the past, and it is biased by the time-dependency i.e. an older paper has the probability of obtaining more citations than a newer one. Bibliographic coupling is often used to aggregate papers by similarity, and it “measures the similarity between papers through their common cited references” ( Todeschini and Baccini, 2016 ). The advantage of a bibliographic coupling is to compare recent papers even if not been cited yet. The analysis of the co-occurrence of keywords uses the article’s keywords to investigate the conceptual structure of a field. According to Caputo et al. ( Caputo et al. , 2019 ):

This is the only bibliometric method that uses the content of the articles to directly measure similarity in which others use indirect measures such as citations and authorships, co-word analysis is particularly powerful and appropriate to develop a semantic map that helps in understanding the conceptual structure of a field.

By comparing and contrasting the results from activity indicators, co-citation analysis, bibliographic coupling and co-occurrence of keywords, it is possible to provide a systematic overview of the field ( Caputo et al. , 2021 ). The activity indicators will show the evolution of the field and its impact. Co-citation and bibliographic coupling will show an unbiased view of the most influential articles, authors and journals, whereas the co-occurrence of keywords will show the thematic map of the topics investigated.

The software VOSViewer ( van Eck and Waltman, 2010 ) was used to calculate the bibliometric indicators and provide the graphic representation of the networks. For a detailed explanation of the scripts and mathematical algorithms adopted in VOSViewer, please see van Eck and Waltman (2007 , 2010 ).

Combining the results of co-citation analysis and bibliographic coupling allowed us to identify a list of the most influential papers that were then considered for the qualitative systematic literature review. We have combined the top 20 papers resulting from three indicators: absolute citations, normalized citations and bibliographic coupling strength. Absolute citations are represented by the total number of citations received by a paper. Normalized citations are represented by the number of citations of the paper divided by the average number of citations of all papers published in the same year and included in our data set ( van Eck and Waltman, 2016 ). The bibliographic coupling strength is measured by the bibliographic coupling total link strength algorithm in VOSViewer, indicating the level of similarity and interconnectedness of a paper in the field regardless of the received citations ( van Eck and Waltman, 2016 ). Integrating these three measures allows us to reduce the age bias of papers and include in the evaluation the influence of a paper, not only the number of citations received but also how the content of the paper relates to other papers in the same scientific community.

The resulting data set of unique papers in the top 20 list from each indicator is composed of 41 papers, which constituted the data set for the literature review.

Having selected the most influential articles to review, we proceeded to the literature review based on the content analysis of selected papers ( Duriau et al. , 2007 ). Following best practices, each article was read in full and analyzed qualitatively ( Barclay et al. , 2011 ; Pittaway and Cope, 2007 ). Articles were coded, tagged and later grouped into clusters based on their content; the articles were allowed to be part of more than one cluster ( Caputo et al. , 2016b ). The process was dynamic, allowing new tags to be included during the process of reading articles to allow flexibility in categorizing information and reducing biases that may arise from a rigidly pre-set system ( Caputo et al. , 2016b ; Dabić et al. , 2020 ). Short and Palmer (2008 , p. 279) categorize content analysis into three methods: “human-scored systems, individual word-count systems, and computerized systems that use artificial intelligence”. We combined computer-aided techniques with human-scored techniques, integrating rigor and insights from the bibliometric analyses with the interpretation of researchers.

3. Results of the bibliometric analyses

3.1 activity bibliometric indicators.

Our bibliometric analysis confirms a constant growth of attention to the handling problems in VTs over time with an increasing number of journal outlets.

Figure 1 shows how the field started in 2001 and is in a growing directory, although the number of papers published is still limited, making the study of conflict in VTs a niche.

In terms of journals, 58 unique outlets have published 107 papers in the data set. Table 1 shows the 20 most cited journals and indicates also the number of published papers and average citations received by them. In terms of total citations, Organ Sci., Acad. Manage. J., J. Manage. Inform. Syst., J. Int. Bus. Stud. and Inf. Manage., are the most influential outlets. However, if we consider the number of papers published, which is a proxy of the interest of a journal on the topic, Small Group Res., J. Manage. Inform. Syst., Organ Sci., Inf. Manage. and J. Manag. are the five most interested journals. Instead, looking at the impact of the individual articles, the situation changes again with J. Int. Bus. Stud., Acad. Manage. J., Organ Sci., Int. J. Confl. Manage. and Inf. Manage. It can be noted how Organization Science and Information Management are the journals appearing in the top five in all three measures.

Looking at the authors, 290 scholars have authored the 107 papers in the data set. Out of these, only three, Ahuja, Staples and Zornoza, have authored at least three papers and can, therefore, be considered the most prolific in the field. Table 2 lists the most prolific authors who have authored at least two papers. Interestingly, if we look at the most cited authors, only three of them (Hinds, Majchrzak and Staples) appear in the top 10 of most cited ( Table 3 ).

The studies in the data set were authored by affiliates of 186 research institutions from 28 different countries. The research in the field of conflict in VTs appears to be predominantly made in the USA (65 papers) and other western countries.

3.2 Co-citation analysis: the foundations of the field

The co-citation analysis is a powerful tool to investigate the foundations of the research about conflict in VTs through the analysis of the references cited by the papers in our data set. The analysis reveals those that are the most cited references, authors and journals. Table 4 shows the statistics and criteria used for the co-citation analysis.

By performing a co-citation analysis, we were able to identify the 10 most cited papers, authors and journals that constitute the theoretical pillars of the research on the conflict in VTs. The results show how such research is grounded in the literature about VTs and remote working ( Cramton, 2001a ; Jarvenpaa and Leidner, 1999 ) pillar studies in conflict management ( Jehn, 1995 ) and the early studies integrating the two ( Hinds and Bailey, 2003 ; Mortensen and Hinds, 2001 ).

A combined reading of the most influential cited references and the network of similarities ( Figure 2 ) show that the research about conflict in VTs relies on a coherent and homogeneous network grounded in the scientific community of the fields of management and organization studies ( Table 5 ).

3.3 Bibliographic coupling: the structure of the field

Bibliographic coupling analysis is used to evaluate the current structure of a field based on a clustering technique that allows us to compare recent papers even if not yet cited; therefore, not being biased by time. However, the method has severe limitations in cases like ours that analyze smaller research fields ( Jarneving, 2007 ); hence, the technique was adopted to complement citation and co-citation analysis and was not used to create clusters but rather to identify the network relevance of papers, authors and journals. All papers (107), authors (290) and journals (58) from the data set were included in the analysis ( Figure 3 ) ( Table 6 ).

By performing a bibliographic coupling analysis, we were able to identify the 10 most connected papers, authors and journals that constitute the current structure of the research in the conflict in VTs. Via the visualization of networks technique, is it also possible to show how the field is well interconnected across the three levels of analysis, confirming the finding that the research about conflict in VTs relies on a coherent and homogeneous scientific community.

3.4 Co-occurrence of keywords

The analysis based on the co-occurrence of keywords allows us to show the intellectual structure of the field by identifying and grouping the main topics that have been subject to investigation. This method is particularly useful to complement the previous analysis as it offers a direct measure of similarity of topics by analyzing the actual content of the papers via the keywords.

The keyword analysis was performed by adopting the Keyword Plus tool from WoS. Even though the Keyword Plus is usually chosen to ensure consistency across the classification of articles’ keywords, it was necessary to perform a manual harmonization of the spelling of those keywords.

Previous studies have considered Keyword Plus to be effective as the keywords provided by the authors in terms of bibliometric analysis, investigating the knowledge structure of scientific fields ( Zhang et al. , 2016 ). The adoption of Keyword Plus allows the researcher to limit biases and risks associated with the manual tagging of content. Only keywords that occurred at least five times were kept; this resulted in having only 39 keywords to constitute the largest usable set of connected terms ( Table 7 ).

The network diagram and overlay visualization of the keywords ( Figure 4 ) show that the intellectual structure of the topics is quite homogeneous and has evolved. In particular, the research on conflict in VTs started with the investigation of technological topics and issues related to cultural diversity, personality and leadership.

3.5 Synthesis of results

Having shown the individual results of activity indicators, co-citation, bibliographic coupling and co-occurrence of keywords, we moved our attention to a synthesis that allowed us to identify the most influential papers to be included in the systematic literature review.

Table 8 shows the top 20 articles according to three complementary metrics: the normalized citations, the total citations and the link strength. The total citations are computed by counting all citations received by a paper in the WoS Core Collection at the time of the study. The normalized number of citations in a paper equals the number of citations in the paper divided by the average number of citations of all papers published in the same year and included in the data set ( van Eck and Waltman, 2016 ). The total link strength indicates the total strength of the links of an article with the other articles in the data set calculated via the bibliographic coupling analysis ( van Eck and Waltman, 2016 ). By comparing these three measures, we can countereffect the biases of each of them in terms of age of the article, relative impact and connectedness in the field. As a result, 41 unique articles were discovered to be included in at least one of the metrics and formed the basis for our systematic literature review.

4. Systematic literature review

This section presents the results of the systematic literature review that has been based on the most influential articles belonging to each cluster and the classification obtained by analyzing the content of each article. We have identified five thematic clusters: trust, performance, cultural diversity, knowledge management and team management.

4.1 Trust cluster

The issue of trust is among the key topics in conflict and conflict management studies ( Caputo et al. , 2019 ). Trust is an extremely important variable for successful collaboration ( Donovan, 1993 ) and increased relational capital ( Connelly and Turel, 2016 ). Nevertheless, trust is also regularly perceived as a challenging issue for team effectiveness ( Breuer et al. , 2016 ), particularly under virtuality, due to the lack of clarity on interaction mechanisms ( Bierly et al. , 2009 ; DeRosa et al. , 2004 ). Being a crucial construct for any variation of teams, trust is proved as more difficult and important to achieve in the circumstances of physical dispersion of team members ( Brahm and Kunze, 2012 ; Breuer et al. , 2016 ; Connelly and Turel, 2016 ; Staples and Webster, 2008 ; Yakovleva et al. , 2010 ). Peñarroja et al. (2013) concluded that the level of virtuality negatively influences team trust, whereas trust is also vital for reducing both interpersonal and task conflicts ( Connelly and Turel, 2016 ; Curseu and Schruijer, 2010 ) as well as for successful conflict management processes ( Bierly et al. , 2009 ). Virtuality is mainly considered to be a moderating variable in the relationship between trust and conflict ( Bierly et al. , 2009 ), where trust may be both an output and an input of the group processes, such as conflict ( Marks et al. , 2001 ). A further explanation is provided by studies that determined that the greater the degree of virtuality, the greater the negative impact on trust by relationship conflict ( Bierly et al. , 2009 ; Peñarroja et al. , 2013 ). In this vein, Breuer et al. (2016) showed that a high degree of virtuality increases internal team risks that in turn increase the necessity for trust, thus forming a loop relationship between a group functioning, conflict and trust ( De Dreu and Weingart, 2003 ). In general, the relationship between team functioning, conflict and trust could be described as a negative association between conflicts and trust exacerbated by the degree of virtuality ( Bierly et al. , 2009 ; Polzer et al. , 2006b ).

4.2 Performance cluster

The next cluster is based on team performance which is considered to be highly influenced by internal team communication in VTs ( Massey et al. , 2014 ; Montoya-Weiss et al. , 2001 ; Sarker et al. , 2011 ). VTs have different characteristics than traditional teams ( Brahm and Kunze, 2012 ), and it was found that people are capable of adapting to the conditions of VTs, such as restricted communication channels, probable instability of internet connection and lacking opportunities for informal communication ( van der Kleij et al. , 2009 ). Moreover, video communication and similar technologies reduce the main differences between teams that are co-located and geographically dispersed teams ( Bradley et al. , 2013 ). A great number of studies have shown that geographical distance between team members may complicate conflict management ( Cramton, 2001b ; Hill and Bartol, 2016 ). However, the extensive usage of mediated communication technologies may exaggerate the negative impacts of conflict in teams ( Kankanhalli et al. , 2006 ) due to complexities such as the unavailability for frequent discussions, information exchange and clarifications regarding personal and task issues, which may result in misunderstandings and further communication closure ( Mortensen and Hinds, 2001 ). In other words, virtuality increases the complexity of the triggers and the dynamics of conflicts as well as their management and resolution ( Friedman and Currall, 2003 ). In turn, such communication complexities among team participants (conflicts) negatively influence team performance ( Connelly and Turel, 2016 ; Turel and Zhang, 2010 ). However, the understanding of the underlying mechanisms of how conflicts work and their influence on team performance in VTs still demands additional research ( Connelly and Turel, 2016 ). There are several debates about the impact of conflict on VT performance. For instance, Hinds and Mortensen (2005) state that the virtuality of teams increases the vulnerability to conflicts due to the lack of casual, unplanned communication between team members, which, in turn, negatively influences the overall team performance. However, in a review of the literature, Ortiz de Guinea et al. (2012) emphasize contrasting findings where virtuality and performance correlate both in positive and negative directions. The recent body of research regarding conflicts and team performance in VTs admits that virtuality should be perceived as a continuous rather than binary variable to avoid clashing results ( Griffith et al. , 2003 ; Malhotra and Majchrzak, 2014 ; Ortiz De Guinea et al. , 2012 ). It was discovered that a level of virtuality should include distance indicators of separation, the configuration of a proportion working virtually and face-to-face and time parameters of virtual collaboration ( Ortiz De Guinea et al. , 2012 ). For studies looking at team performances, it is crucial to consider contextual conditions, degrees of virtuality and mediating technologies as they may significantly alter the relationship ( Malhotra and Majchrzak, 2014 ). For example, research where virtuality is treated as a continuous variable shows less presence of conflicts in more VTs and no impact on the performance ( Ortiz De Guinea et al. , 2012 ). Kankanhalli et al. (2006) propose a theoretical framework where both task conflict and relationship conflict do not have a direct influence on VT performance, contingent upon the conflict resolution approach (for both), task complexity (for task conflict) and task interdependence (relationship conflict). Looking at conflict management, research has indicated that the conflict management style ( Paul et al. , 2004b ) and conflict management behavior ( de Dreu and van de Vliert, 1994 ; Montoya-Weiss et al. , 2001 ) are critical conditions for successful team performance in the dimension of virtual collaboration. Additionally, collaborative conflict management style was indicated as a positive influencing factor on team performance, whereas group heterogeneity was found to be a barrier to successful conflict management and effective group performance ( Paul et al. , 2004b ).

4.3 Cultural diversity cluster

Cultural diversity is one of the most ambiguous concepts regarding communication, teams and organizational studies. A series of meta-analyses validate this point stressing the nature of the complex notion to be both a benefit and a challenge ( Smith et al. , 1994 ; Stahl et al. , 2010 ). In the context of teams and team working, cultural diversity refers to the different cultural backgrounds of the team members ( Harush et al. , 2018 ), including diversity in nationality ( Gibbs et al. , 2017 ) and broader cultural aspects ( Kankanhalli et al. , 2006 ), such as linguistic diversity ( McDonough et al. , 1999 ) and cultural dimensions ( Hofstede, 1991 ). As a concept, cultural diversity is perceived as a key to a greater and innovative performance ( Polley and McGrath, 1984 ) or the contrary, as a reason for ingroup miscommunications ( Brett et al. , 2006 ; Staples and Zhao, 2006 ). Globalization dynamics and technological advancements ( Paul et al. , 2004b ) are increasing virtuality and multiculturality in teams ( Gibson et al. , 2014 ), resulting in the prevalence of geographically dispersed international teams over face-to-face ones ( Stahl et al. , 2010 ). The combination of physical dispersion and cultural diversity ( Shachaf, 2008 ) increases the complexity of VTs due to the more radical differences between team members’ attitudes and perceptions ( Zimmermann, 2011 ). As a result, communication and the gaining of possible benefits associated with diversity may become more problematic ( Gibson and Gibbs, 2006 ). Implementing cultural diversity may result in misunderstandings and conflicts between team members ( Maznevski et al. , 2006 ; Paul et al. , 2004b ; Stahl et al. , 2010 ) due to reasons such as the communication ( Shachaf, 2008 ) and social categorization ( Harush et al. , 2018 ). Hence, conflict management is of significant importance as often team dynamics are complicated not only in the virtual settings but also by the cultural heterogeneity ( Paul et al. , 2004a ; Paul, Seetharaman, et al. , 2004b ). The debate whether cultural diversity increases or decreases conflicts in VTs is continuing ( Kankanhalli et al. , 2006 ; Mortensen and Hinds, 2001 ). Kankanhalli et al. (2006) discovered from their in-depth study that cultural diversity in VT leads to relationship and task conflicts, which they explain by the similarity attraction theory ( Wells and Aicher, 2013 ) and social identity theory ( Ashforth and Mael, 1989 ). Usage of the latter theory is also supported by Mortensen and Hinds (2001) and Harush (2018) , who emphasized the vital role of forming a global identity as a self-categorization process to a shared team ingroup identity to reduce the level of relational conflicts in GVT’s environment, especially in the circumstances of low task interdependence. Paul, Seetharaman, et al. (2004b) support the negative impact of team members’ cultural diversity on conflict resolution processes and group interactions due to the variations in values. Furthermore, Staples and Zhao (2006) concluded that culturally diverse teams indicated lower levels of satisfaction and cohesion and higher levels of conflicts. However, it was also pointed out that culturally diverse VTs showed higher performance rates and fewer conflicts than face-to-face ones. This finding emphasizes the importance of taking under consideration not just every separate characteristic of a team but the combinations of the teams’ settings. Whilst to some, cultural heterogeneity of teams can negatively impact interactions and communication processes, increasing conflicts ( Pelled, 1996 ), to others, diversity can be very beneficial for teams’ dynamics and conflict reduction ( Staples and Zhao, 2006 ). These opposing viewpoints could be explained by several factors. For instance, Paul et al. (2004a) , in contrast to a widespread belief about the negative impact of cultural diversity on group dynamics, found that higher levels of agreement within international groups could be achieved by conflict management ( Paul et al. , 2004a ) and relevant media choices ( Klitmøller and Lauring, 2013 ). Additionally, according to Stahl et al. (2010) , the physical dispersion of team members tends to moderate the impact of cultural diversity on conflicts as the virtual international teams showed lower levels of conflicts and higher social integration compared with multicultural collocated teams. These findings were similarly indicated by Mortensen and Hinds (2001) in their earlier research with the reason that the notion of reduced conflicts could be a result of either stronger ingroup integration or an adverse environment for conflicts to arise.

4.4 Knowledge management cluster

Efficient knowledge management is vital for the success of a company, project or team ( Chiravuri et al. , 2011 ). The process of knowledge transferring, sharing and exchanging provides additional challenges for collocated teams ( Ortiz De Guinea et al. , 2012 ). Due to the globalization dynamics, knowledge sharing between geographically distributed team members and experts has become an integral part of international companies and VTs ( Raab et al. , 2014 ). Consequently, knowledge management in VTs and presumed conflicts came to the scholars’ attention due to the complex settings of geographically distributed teams. The implied challenges are explained as difficulties in sharing comprehensive knowledge with no face-to-face communication potentially creating sub-groups ( Boh et al. , 2007 ) and reducing the attention of team members under virtual circumstances ( Ortiz De Guinea et al. , 2012 ). This, in turn, may lead to misunderstandings ( Hinds and Bailey, 2003 ), failure of information sharing ( Hinds and Mortensen, 2005 ) and other interpersonal difficulties ( Boh et al. , 2007 ). Ortiz De Guinea et al. (2012) argue that the predominantly multicultural composition of geographically dispersed teams issues such as language diversity may jeopardize the knowledge sharing process and boost the frequency of conflicts. Chiravuri et al. (2011) indicated that a combination of a lack of face-to-face cues ( Klitmøller and Lauring, 2013 ) and probable culturally contrasting behavioral models can cause different patterns of information exchange, which in turn leads to misunderstandings ( Cramton, 2001b ; Kayworth and Leidner, 2002 ) and conflicts during the knowledge capture process. At the end of the study, the authors emphasized a repertory grid cognition-based technique (“cognitive mapping technique that attempts to describe how people think about the phenomena in their world” [ Tan and Hunter, 2002 , p. 40]) as a reliable measure for decreasing conflicts in VTs in the knowledge capture process ( Chiravuri et al. , 2011 ). Furthermore, Klitmøller and Lauring (2013) put a value on the multicultural element of VTs and its important role in the process of selecting particular types of media for knowledge exchange (e.g. using a rich media for more ambiguous matters and a lean media in case of canonical knowledge exchange). Raab et al. (2014) researched the mechanisms of knowledge sharing in a globally dispersed context identifying a link between the imbalance of the geographical distribution of group members and the low efficiency of knowledge sharing due to the strong social categorization processes ( Polzer et al. , 2006a ) and potential conflicts between subgroups ( Fiol and O’Connor, 2005 ; Hinds and Mortensen, 2005 ). Indeed, a proper mix of technological and organizational elements is believed to be crucial for proper knowledge exchange, open knowledge sharing and all other issues connected to knowledge management in the conditions of virtual collaboration ( Zammuto et al. , 2007 ). Tools of virtual communication may reduce cultural differences ( Stahl et al. , 2010 ) and positively impact knowledge-sharing processes ( Klitmøller and Lauring, 2013 ).

4.5 Team management cluster

“E-communicational”, i.e. a manager positions himself as a part of a VT and takes under consideration teleworking specificities maintaining informal communication, interpersonal trust, increasing perceived proximity and also exposing a strong shared identity that tends to prevent conflicts ( Mortensen and Hinds, 2001 ); and

“Control mode”, i.e. managers are not co-teleworkers as they manage VTs prevailingly, focusing on work objectives with high levels of institutionalization and formalization.

On the one hand, managerial interference may impede establishing social connections between group representatives ( Gulati, 1995 ). On the other hand, managers should intervene in the virtual setting of a team, stimulating frequent and effective communication. In this way: team members could build better social relationships ( Malhotra et al. , 2007 ; Raab et al. , 2014 ; Saunders and Ahuja, 2006 ) and not experience conflicts due to obstacles in the technological adaptation ( Thomas and Bostrom, 2010 ). The latter claim is also supported by Chiravuri et al. (2011) , who consider that a manager has to be involved in the in-group processes to discern the nature of conflicts. In the case of a cognitive conflict, this should be closely monitored as it is capable of causing either stagnation of the process or improved solutions ( Chiravuri et al. , 2011 ). In the study by Raab et al. (2014) , managerial involvement was found to be a mitigator of cultural boundaries but had no moderating effect on the relationship between trust and satisfaction with knowledge sharing in globally dispersed groups. Thus, managers may be concerned with tracking the essence and type of a conflict in VT’s dynamics and implementing appropriate conflict management techniques to increase the productivity of a project.

5. Setting-up a research agenda

The purpose of this paper is the systematization of the accumulated knowledge of the field and, because of that, paving interesting and promising research avenues ( Caputo et al. , 2018b ; Tranfield et al. , 2003 ), especially about the results of the systematic literature review, the clear focus characterizing research of emerging conflicts and conflict management in VT, and these are interpreted in a framework stressing possible interconnections and relationships among them.

The logic of the framework is consistent with the traditional input-process-output (IPO) approach to studies on VT and has been used in previous systematic literature reviews ( Garro-Abarca et al. , 2021 ; Gilson et al. , 2015 ). Differently from that, however, the linearity of a pure IPO logic did not emerge from the results of that literature. For this reason, our interpretative framework cannot postulate a single or cause-effect directionality between its theoretical blocks, hypothesizing fuzzy and yet to be untangled relationships. The “fuzziness” refers to a nonlinearity, i.e. a block seems to have several impacts on others e.g. direct, indirect, moderated or mediated effects; recursive relationships, i.e. most of the blocks have bi-directional relationships with the others; thus, self-reinforcing loops based on previous interaction either positive and negative may occur; configurational approach, i.e. a single block when considered in isolation seems to hold a limited explanatory power, and better results would be achieved analyzing several factors together. Thus, it would be reasonable to say that it is not so much the presence or the intensity of a single element/block to determines the outcomes but the co-presence or, conversely, the co-absence of a set of elements that is the key interpretation. In Figure 5 , we only adopted the categorization of the IPO framework, specifically the antecedents, dynamics and outcomes, and we also depicted rippled lines among these categories to represent the fuzziness of these relationships. However, any category of the theoretical blocks potentially influences and is influenced by the others; thus, the arrows are present at both ends of the lines.

The first category of antecedents is fixed elements that come from the structural contingencies in which a VT operates its composition. These structural elements refer to the demographic, cultural and individual characteristics of team members, and they can be grouped under the umbrella concept of the heterogeneity existing in a team. This heterogeneity is the root of several latent or actual conflicts and conflict-related dynamics that may affect individual team members or the whole group ( Schaubroeck and Yu, 2017 ). For example, different personalities or intensity of traits, e.g. consciousness and extraversion, may increase or lessen dyadic conflicts among members ( Turel and Zhang, 2010 ). However, these elements do not affect only conflicts but also shape different strategies to manage them, opening the debate to a contingent and contextual approach to conflict management in VTs. As evidenced from the thematic clusters, heterogeneity may pertain to different cultural backgrounds that may hinder the process of cohesion due to the homophily phenomenon, thus preferring individuals with similar characteristics or common shared culture. This stimulates the formation of sub-groups ( Gibson and Gibbs, 2006 ), highlighting the necessity of specific strategies to reduce conflicts and the fault-lines within a team. Heterogeneity, however, is a broader concept than merely culture ( Boh et al. , 2007 ). As the geographical dispersion of team members increases, the higher is the likelihood of having team members with diverse institutional, economic and other contingencies that may stimulate an increment of conflicts, stricter management of them and other problems in the functioning of a team ( Jimenez et al. , 2017 ). This heterogeneity may directly influence a team or individual performance, but its indirect effect via conflicts, conflict management strategies and functioning processes of a team are still yet to be explored (dynamics). Future research avenues could inquire what type of heterogeneity factors can have a different impact in VT from those traditionally stressed for co-located teams. Even more interesting could be a study of whether heterogeneity plays a different role in the strategy to manage those conflicts or affect the team functioning of a VT in different ways. For instance, are these potential tensions more marked in VTs related to the fact that interactions are less frequent and with less embedded exchanges ( Hinds and Bailey, 2003 )? Conversely, as individual differences seem to play a minor role in VTs, can these tensions be lessened when in co-located teams ( Wakefield et al. , 2008 )? Paying attention to the heterogeneity of a VT also holds strong implications for practice; managers and leaders should first carefully design the composition of a VT not only for reasons of technical competencies but also of cultural and soft skill aspects related to the team members. This may reduce potential conflicts at several levels. Second, even if a proper design is not implementable, the heterogeneity of a VT should be fully acknowledged to counterbalance the tendency to disengage.

The second category of this interpretative framework is represented by what has been termed as dynamics, as all these elements pertain to interactions among members and the several processes through which VT functions and performs ( Breuer et al. , 2016 ). In our framework based on identified clusters, we consider these categories: the conflicts, in terms of their nature and level of impact, the conflict management process and other relevant dynamic interactions occurring in a team, called team functioning that specifically includes the process of building trust and that of managing knowledge flows. As premised, the fuzziness of these relationships also reveals that blocks of the same category have internal relationships e.g. conflict management impacts, and is impacted by, the characteristic of conflicts in VTs and by the team functioning elements of VTs. Similarly, we expect conflicts to impact team functioning directly and via the various degrees of conflict management and vice versa.

In terms of conflicts in VTs, discrimination should be made of the nature of the conflict. Virtuality, on the one hand, may stimulate relational conflicts, as misunderstandings in communication and lack of trust occur more readily ( Hinds and Bailey, 2003 ). Caputo et al. (2019) , in a bibliometric overview of conflict management studies, highlighted the important role of culture in the relationship between trust and conflict. It is expected that building trust and managing trust-based conflicts are more complex in virtual settings due to their enhanced multicultural composition and the difficulty for individuals to decodify clues in a virtual environment. However, in task-based conflict, such a clear negative influence does not seem so prominent ( Gibbs et al. , 2017 ). To summarize, can conflicts of different nature be affected by virtuality, and in which ways? Are there interactional effects? Similarly, the specific level at which conflicts are embedded is also relevant. Conflicts may spur at an individual level, for example, a team member that has to juggle between work and personal life ( Clark, 2000 ). The Covid-19 pandemic poses serious questions about the ambivalence of flexible work arrangements and also in VTs, especially concerning team members with care duties ( Hilbrecht et al. , 2008 ). Conflicts can be related to a dyadic sphere from a faction of the team members to the whole group ( Park et al. , 2020 ). These different levels are not well addressed in team literature, and the virtuality adds complexity to the debate. How do individual, dyadic and group-level conflicts influence each other? How does virtuality impact the propagation of a specific level of conflict onto others? Is it stronger or more insulated?

Conflict and conflict management strategies should also be clear prerogatives of the leaders of VT. Leaders should determine the specific nature and level of impact of this conflict to design proper conflict management strategies. Escalating or de-escalating strategies should be in place to keep a high level of engagement and other team dynamics.

There are several dynamic processes, such as communication ( Jarvenpaa and Leidner, 1999 ), leadership ( Hill and Bartol, 2016 ) and temporality ( Saunders and Ahuja, 2006 ), all of which may cause or redeem conflicts in VTs. In turn, when properly (or poorly) executed, these dynamics create sediment (or detriment) for social identification and trust, fueling (or hindering) any further in-group interactions, exchanges and conflicts ( Brahm and Kunze, 2012 ; Harush et al. , 2018 ). Future studies are required to untangle the nexus between such dynamics, especially as moderators and mediators ( Gilson et al. , 2015 ). This is also true about the structural elements: are there joint processes influencing each other to cause conflicts? In addition, as Garro-Abarca et al. (2021) highlighted, the Covid-19 pandemic has quickly changed organizational routines moving traditional co-located teams into the virtual space. Did the changes induced by the pandemic create alternative processes and their related conflict? Does a “new normal” exist in which processes will be managed differently from the past, blending elements of virtuality into traditional teams? All these considerations are research avenues to be considered.

Virtuality, in general, seems to reduce the ability of a VT to manage knowledge ( Raab et al. , 2014 ), but some positive effects have also been depicted ( Klitmøller and Lauring, 2013 ). These contrasting results are probably because knowledge management is a broad concept traditionally articulated in sub-processes: knowledge acquisition, creation, sharing or transferring, accumulation or retrieving and application or usage ( Inkinen, 2016 ). Each of these processes may be influenced differently from virtuality, the heterogeneity of the team and the other team functioning dynamics. For example, knowledge sharing is reinforced by participative leadership styles ( Pellegrini et al. , 2020 ), but participation and engagement may be reduced in VT due to latent conflicts. Conversely, knowledge accumulation in a virtual environment may be enhanced as to properly function; most VTs need a large stock of codified knowledge. Thus, future studies should address the relationships between every single process of knowledge management and their interactional effects with the antecedents of conflicts, the type and level and strategies to manage them, not forgetting to consider the indirect and interactional effects of other team functioning processes. To summarize, how do the different processes of knowledge management relate to conflicts, conflict management strategies and team functioning in a VT context? Future studies may consider the fast-changing technological environment of the past decade, for example, considering the advent of the 4.0 revolution. If more inclusive and far-reaching information and communications technology tools alleviate the differences between co-located and VTs ( Bradley et al. , 2013 ), the sophisticated approaches of the 4.0 such as the Internet of Things ( Caputo et al. , 2016a ), big data ( Rialti et al. , 2020 ) and artificial intelligence algorithms may offer interesting modifications about the impact on knowledge management and team performance in general ( Manesh et al. , 2020 ). How will the 4.0 revolution affect conflicts in VTs?

Considering the practical implications related to several teams’ functioning processes, leaders may consider constructing a managerial grid to keep control of either the individual performance or the overall group-level results. These ongoing evaluations can help to detect conflicts earlier and thus structure a proper conflict management strategy.

Considering the final category of outcomes, conflicts have been generally studied concerning their negative impacts on the performance of VTs. Virtuality tends to exacerbate conflicts and may reduce the consequentially a VT’s performance ( Hinds and Mortensen, 2005 ). However, as already presented in this framework, a relationship of linearity must be excluded. Too many other co-factors may intervene due to the heterogeneity of the composition of the team, the way conflicts are handled, and their impacts on other crucial dynamics. Conflicts cannot be reduced in this univocal direction ( Ortiz De Guinea et al. , 2012 ). Future studies are, thus, invited to clearly define their performance variables and hopefully consider virtuality as a continuum ( Malhotra and Majchrzak, 2014 ) to avoid partial conclusions. Adopting this framework, interesting avenues may be explored about the interactional effects of its several theoretical building blocks. For example, does the different nature of conflicts impact differently on performance? Are these impacts also affected by the specific sources of conflicts (processes of latent elements)?

Further future research avenues may also come from the adoption of newer methodologies in the field of conflict management, such as fuzzy-set qualitative comparative analysis (fsQCA), a methodology we could not find in the analyzed data set but that is receiving growing attention in management research ( Kraus et al. , 2018 ; Pappas et al. , 2021 ). FsQCA is a set-theoretic approach that is used to investigate complex causality, and therefore, allows for the identification of specific combinations of conditions called configurations that are nonexclusive and lead to the same outcome ( De Crescenzo et al. , 2020 ; Ragin, 2008 ). Future studies could use fsQCA to test empirically our proposed framework allowing the complexity of conflict and conflict management in VTs to be investigated.

6. Conclusion

This paper presents the results of an investigation into the existing literature published over the past two decades about conflict management and VTs. To provide a thorough and systematic analysis in support of the growing needs of managing virtual workforces and projects, innovative bibliometric methods have been deployed, displaying an overall view of the field of research and a systematic review has provided us with the details of the five identified thematic clusters enabling a holistic framework to be developed. Results have shown the importance of the interlinkages between the five clusters such as trust, performance, cultural diversity, knowledge management and team management are well-defined topics that rely on each other’s findings for advancing knowledge and practice.

Although this study adopted a rigorous and systematic methodology of review, some limitations remain. Specifically, a limitation may lie in focusing on management studies that contribute to focusing and positioning the paper in a clear discipline of research and homogeneity of data, but it may result in overlooking contributions from other fields. Moreover, to fulfill the need for homogeneity of bibliographic data, the study focused only on published journal articles omitting books, book chapters, conference papers and nonpeer-reviewed papers. This limitation is balanced by the higher quality and rigor of studies that have been peer-reviewed and future studies, perhaps using a meta-analytic approach, may also consider these outputs. As in previous systematic review studies, our study has been privileged to offer a wider overview and research agenda rather than deepening into fine-grained details. However, as this tradeoff is a natural consequence of review studies, our review and agenda offer a solid ground for future studies to build upon and further advance our knowledge of conflict management in VTs, satisfying the latest needs of organizations and societies linked to the increase in remote working conditions.

Number of papers published per year

Network diagram of co-citation analysis

Network diagram of bibliographic coupling analysis

Network diagram and overlay visualization of keywords

A framework for conflict management in virtual teams

Most cited journals

Most prolific authors

Most cited authors

Criteria of the co-citation analysis

Co-citation analysis

Bibliographic coupling analysis

Main topics from the co-occurrence of keywords analysis

Most influential articles

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Corresponding author

About the authors.

Andrea Caputo is an Associate Professor in Management at the University of Trento, Italy, and at the University of Lincoln, UK, where he is part of the UNESCO Chair in Responsible Foresight for Sustainable Development. His main research interests include entrepreneurial decision-making, negotiation, digitalization and sustainability, internationalization and strategic management of SMEs. He is the editor of the book series “Entrepreneurial Behaviour” (Emerald), and Associate Editor of the Journal of Management and Organization. His research was published in over 100 contributions, including articles in highly ranked journals, e.g. HRM Journal , Journal of Business Research, Small Business Economics , International Journal of Conflict Management , Journal of Knowledge Management , Business Strategy and the Environment and IEEE TEM among the others.

Mariya Kargina is a PhD Candidate in Organizational Behavior at the University of Rome “Tor Vergata”. She holds a Master of Science from the University of Lincoln, UK. Her research interests are cross-cultural management, cultural intelligence and global virtual teams. Her research was published in the Journal of Marketing Analytics and presented at several international conferences.

Massimiliano Matteo Pellegrini is an Associate Professor of Organizational studies and Entrepreneurial behaviors at the University of Rome “Tor Vergata”. Previously, he worked at Roehampton University Business School and University of West-London. He is the editor of the book series “Entrepreneurial Behaviour” (EmeraldPublishing), Associate Editor at International Journal of Transition and Innovation System, and past Chair of the Strategic Interest Group of Entrepreneurship (E-ship SIG) at the European Academy of Management (EURAM). He published in highly ranked journals as e.g. Journal of Business Research , Small Business Economics , Journal of Business Ethics , IEEE Transaction on Engineering Management and Journal of Small Business .

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Communication in virtual teams: a conceptual framework and research agenda

2017, Human Resource Management Review

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Virtual Teams and Management Challenges

Academic Leadership Journal, 9(3), pp. 1-7, Summer 2011

7 Pages Posted: 19 Apr 2012

Nader Ale Ebrahim

Research and Technology Department, Alzahra University, Vanak, Tehran, Iran, Postcode: 19938 93973; Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM); University of Malaya (UM) - Department of Engineering Design and Manufacture

Shamsuddin Ahmed

University of Malaya (UM)

Zahari Taha

Date Written: 2011

Collaboration is becoming increasingly important in creating the knowledge that makes business more competitive. Virtual teams are growing in popularity [1] and many organizations have responded to their dynamic environments by introducing virtual teams. Additionally, the rapid development of new communication technologies such as the Internet has accelerated this trend so that today, most of the larger organization employs virtual teams to some degree [2]. A growing number of flexible and adaptable organizations have explored the virtual environment as one means of achieving increased responsiveness [3]. Howells et al. [4] state that the shift from serial to simultaneous and parallel working has become more commonplace. Based on conventional information technologies and Internet-based platforms virtual environments may be used to sustain companies’ progress through virtual interaction and communication.

Keywords: Virtual R&D teams, Virtual Team, Management Challenge, Collaboration, ICT application

JEL Classification: L1, L11, L2, M11, M12, M1, Q1, O1, Q31, Q31, P24, L17, O32, P29

Suggested Citation: Suggested Citation

Nader Ale Ebrahim (Contact Author)

Research and technology department, alzahra university, vanak, tehran, iran, postcode: 19938 93973 ( email ), centre for research services, institute of management and research services (ippp), university of malaya (um) ( email ).

Kuala Lumpur, Wilayah Persekutuan 50603 University of Malaya (UM) Kuala Lumpur, Wilayah Persekutuan 50603 Malaysia

HOME PAGE: http://https://umresearch.um.edu.my/

University of Malaya (UM) - Department of Engineering Design and Manufacture ( email )

Kuala Lumpur, 50603 Malaysia

University of Malaya (UM) ( email )

Kuala Lumpur, Wilayah Persekutuan 50603 University of Malaya (UM) Kuala Lumpur, 50603 Malaysia

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Exploring Major Factors Affecting Virtual Team Performance

• Murat Topaloglu  

Murat Topaloglu

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Ahmet Serhat Anac

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Increasing global operations of companies and advances in communication technologies in the last two decades have led companies to create virtual team, in which employees work more productively and cost-effectively from different locations. This situation required virtual team leaders to have a different perspective and management approach than the leaders who manage teams in the usual offices. Performance management is one of the vital tasks of virtual team leaders and is a multidimensional research topic for researchers interested in virtual team management. Knowing the determinants of performance will be useful in quality decision-making, problem-solving, and many other managerial processes. This research aims to explore major factors affecting virtual team performance by using a systematic literature review methodology that includes more than one hundred scientific articles. Findings of this study suggest that these factors are leadership, communication, collaboration, cohesion, commitment, conflict, interpersonal relations, knowledge sharing, feedback, trust, diversity, recognition, and empowerment.

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Build a Corporate Culture That Works

There’s a widespread understanding that managing corporate culture is key to business success. Yet few companies articulate their culture in such a way that the words become an organizational reality that molds employee behavior as intended.

All too often a culture is described as a set of anodyne norms, principles, or values, which do not offer decision-makers guidance on how to make difficult choices when faced with conflicting but equally defensible courses of action.

The trick to making a desired culture come alive is to debate and articulate it using dilemmas. If you identify the tough dilemmas your employees routinely face and clearly state how they should be resolved—“In this company, when we come across this dilemma, we turn left”—then your desired culture will take root and influence the behavior of the team.

To develop a culture that works, follow six rules: Ground your culture in the dilemmas you are likely to confront, dilemma-test your values, communicate your values in colorful terms, hire people who fit, let culture drive strategy, and know when to pull back from a value statement.

Start by thinking about the dilemmas your people will face.

Idea in Brief

The problem.

There’s a widespread understanding that managing corporate culture is key to business success. Yet few companies articulate their corporate culture in such a way that the words become an organizational reality that molds employee behavior as intended.

What Usually Happens

How to fix it.

Follow six rules: Ground your culture in the dilemmas you are likely to confront, dilemma-test your values, communicate your values in colorful terms, hire people who fit, let culture drive strategy, and know when to pull back from a value.

At the beginning of my career, I worked for the health-care-software specialist HBOC. One day, a woman from human resources came into the cafeteria with a roll of tape and began sticking posters on the walls. They proclaimed in royal blue the company’s values: “Transparency, Respect, Integrity, Honesty.” The next day we received wallet-sized plastic cards with the same words and were asked to memorize them so that we could incorporate them into our actions. The following year, when management was indicted on 17 counts of conspiracy and fraud, we learned what the company’s values really were.

• EM Erin Meyer is a professor at INSEAD, where she directs the executive education program Leading Across Borders and Cultures. She is the author of The Culture Map: Breaking Through the Invisible Boundaries of Global Business (PublicAffairs, 2014) and coauthor (with Reed Hastings) of No Rules Rules: Netflix and the Culture of Reinvention (Penguin, 2020). ErinMeyerINSEAD

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