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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.
- Alaiad, A.; Alnsour, Y.; Alsharo, M. Virtual Teams: Thematic Taxonomy, Constructs Model, and Future Research Directions. IEEE Trans. Dependable Secur. Comput. 2019 , 62 , 211–238. [ Google Scholar ] [ CrossRef ]
- Peñarroja, V.; González-Anta, B.; Orengo, V.; Zornoza, A.; Gamero, N. Reducing Relationship Conflict in Virtual Teams With Diversity Faultlines: The Effect of an Online Affect Management Intervention on the Rate of Growth of Team Resilience. Soc. Sci. Comput. Rev. 2020 , 40 , 388–404. [ Google Scholar ] [ CrossRef ]
- Morrison-Smith, S.; Ruiz, J. Challenges and barriers in virtual teams: A literature review. SN Appl. Sci. 2020 , 2 , 1096. [ Google Scholar ] [ CrossRef ]
- Mysirlaki, S.; Paraskeva, F. Emotional intelligence and transformational leadership in virtual teams: Lessons from MMOGs, Leadersh. Organ. Dev. J. 2020 , 41 , 551–566. [ Google Scholar ] [ CrossRef ]
- Lim, J.Y.-K. IT-enabled awareness and self-directed leadership behaviors in virtual teams. Inf. Organ. 2018 , 28 , 71–88. [ Google Scholar ] [ CrossRef ]
- Dulebohn, J.H.; Hoch, J.E. Virtual teams in organizations. Hum. Resour. Manag. Rev. 2017 , 27 , 569–574. [ Google Scholar ] [ CrossRef ]
- Glikson, E.; Erez, M. The emergence of a communication climate in global virtual teams. J. World Bus. 2020 , 55 , 101001. [ Google Scholar ] [ CrossRef ]
- Peng, C.-H.; Lurie, N.H.; Slaughter, S.A. Using Technology to Persuade: Visual Representation Technologies and Consensus Seeking in Virtual Teams. Inf. Syst. Res. 2019 , 30 , 948–962. [ Google Scholar ] [ CrossRef ]
- Belova, O.L.; Mezhevov, A.D. Virtual Teams in Russian Organizations ; Springer International Publishing: Cham, Switzerland, 2020; pp. 1553–1562. [ Google Scholar ]
- Enrique, G.G.; Joel, M.G. Best practices and opportunity areas for the intelligent management of virtual teams. Manag. Sci. Lett. 2020 , 10 , 3507–3514. [ Google Scholar ] [ CrossRef ]
- Orpinas, P. Social Competence. In The Corsini Encyclopedia of Psychology ; Weiner et, I.B., Craighead, W.E., John, É., Eds.; Wiley & Sons, Inc.: Hoboken, NJ, USA, 2010. [ Google Scholar ]
- Glikson, E.; Woolley, A.W.; Gupta, P.; Kim, Y.J. Visualized Automatic Feedback in Virtual Teams. Front. Psychol. 2019 , 10 , 814. [ Google Scholar ] [ CrossRef ] [ PubMed ] [ Green Version ]
- Davidavičienė, V.; Al Majzoub, K.; Meidute-Kavaliauskiene, I. Factors Affecting Knowledge Sharing in Virtual Teams. Sustainability 2020 , 12 , 6917. [ Google Scholar ] [ CrossRef ]
- da Silva, F.P.; Mosquera, P.; Soares, M.E. Factors influencing knowledge sharing among IT geographically dispersed teams. Technol. Forecast. Soc. Chang. 2022 , 174 , 121299. [ Google Scholar ] [ CrossRef ]
- Zhang, X.; de Pablos, P.O.; Xu, Q. Culture effects on the knowledge sharing in multi-national virtual classes: A mixed method. Comput. Hum. Behav. 2014 , 31 , 491–498. [ Google Scholar ] [ CrossRef ]
- Ryan, R.M.; Deci, E.L. Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemp. Educ. Psychol. 2020 , 61 , 101860. [ Google Scholar ] [ CrossRef ]
- Eseryel, U.Y.; Crowston, K.; Heckman, R. Functional and Visionary Leadership in Self-Managing Virtual Teams. Group Organ. Manag. 2020 , 46 , 424–460. [ Google Scholar ] [ CrossRef ]
- DeChurch, L.A.; Mesmer-Magnus, J.R. Measuring shared team mental models: A meta-analysis. Group Dyn. Theory Res. Pract. 2010 , 14 , 1–14. [ Google Scholar ] [ CrossRef ]
- Liao, C. Leadership in virtual teams: A multilevel perspective. Hum. Resour. Manag. Rev. 2017 , 27 , 648–659. [ Google Scholar ] [ CrossRef ]
- Adamovic, M. An employee-focused human resource management perspective for the management of global virtual teams. Int. J. Hum. Resour. Manag. 2018 , 29 , 2159–2187. [ Google Scholar ] [ CrossRef ]
- Dourish, P.; Bellotti, V. Awareness and coordination in shared workspaces. In Proceedings of the 1992 ACM conference on Computer-supported cooperative work-CSCW ’92, Toronto, ON, Canada, 1–4 November 1992; pp. 107–114. [ Google Scholar ] [ CrossRef ]
- Espinosa, J.A.; Slaughter, S.A.; Kraut, R.E.; Herbsleb, J.D. Team Knowledge and Coordination in Geographically Distributed Software Development. J. Manag. Inf. Syst. 2007 , 24 , 135–169. [ Google Scholar ] [ CrossRef ] [ Green Version ]
- Malhotra, A.; Majchrzak, A. Enhancing performance of geographically distributed teams through targeted use of information and communication technologies. Hum. Relat. 2014 , 67 , 389–411. [ Google Scholar ] [ CrossRef ]
- Hunsaker, P.L.; Hunsaker, J.S. Virtual teams: A leader’s guide. Team Perform. Manag. Int. J. 2008 , 14 , 86–101. [ Google Scholar ] [ CrossRef ]
- Haines, R.; Vehring, N.; Kramer, M. Social Motivation Consequences of Activity Awareness Practices in Virtual Teams: A Case Study and Experimental Confirmation. In Collaboration in the Digital Age ; Riemer, K., Schellhammer, S., Meinert, M., Eds.; Springer International Publishing: Cham, Switzerland, 2019; pp. 89–119. [ Google Scholar ] [ CrossRef ]
- Daassi, M.; Jawadi, N.; Favier, M.; Kalika, M. Building Collective Awareness in Virtual Teams: The Effect of Leadership Behavioral Style. In Leadership in the Digital Enterprise: Issues and Challenges ; IGI Global: Hershey, PA, USA, 2010; p. 23. [ Google Scholar ]
- Walsh, F. Strengthening Family Resilience ; Guilford Press: New York, NY, USA, 1998. [ Google Scholar ]
- Gucciardi, D.F.; Crane, M.; Ntoumanis, N.; Parker, S.K.; Thogersen-Ntoumani, C.; Ducker, K.J.; Peeling, P.; Chapman, M.T.; Quested, E.; Temby, P. The emergence of team resilience: A multilevel conceptual model of facilitating factors. J. Occup. Organ. Psychol. 2018 , 91 , 729–768. [ Google Scholar ] [ CrossRef ]
- Meneghel, I.; Salanova, M.; Martínez, I.M. Feeling Good Makes Us Stronger: How Team Resilience Mediates the Effect of Positive Emotions on Team Performance. J. Happiness Stud. 2014 , 17 , 239–255. [ Google Scholar ] [ CrossRef ]
- Stephens, J.P.; Heaphy, E.D.; Carmeli, A.; Spreitzer, G.M.; Dutton, J.E. Relationship Quality and Virtuousness. J. Appl. Behav. Sci. 2013 , 49 , 13–41. [ Google Scholar ] [ CrossRef ]
- Bowers, C.; Kreutzer, C.; Cannon-Bowers, J.; Lamb, J. Team Resilience as a Second-Order Emergent State: A Theoretical Model and Research Directions. Front. Psychol. 2017 , 8 , 1360. [ Google Scholar ] [ CrossRef ] [ PubMed ]
- West, B.J.; Patera, J.L.; Carsten, M.K. Team level positivity: Investigating positive psychological capacities and team level outcomes. J. Organ. Behav. 2009 , 30 , 249–267. [ Google Scholar ] [ CrossRef ]
- Haas, M.R.; Cummings, J.N. Barriers to knowledge seeking within MNC teams: Which differences matter most? J. Int. Bus. Stud. 2014 , 46 , 36–62. [ Google Scholar ] [ CrossRef ]
- Huckman, R.S.; Staats, B.R.; Upton, D.M. Team Familiarity, Role Experience, and Performance: Evidence from Indian Software Services. Manag. Sci. 2009 , 55 , 85–100. [ Google Scholar ] [ CrossRef ] [ Green Version ]
- Maynard, M.T.; Mathieu, J.E.; Gilson, L.L.; Sanchez, D.R.; Dean, M.D. Do I Really Know You and Does It Matter? Unpacking the Relationship Between Familiarity and Information Elaboration in Global Virtual Teams. Group Organ. Manag. 2018 , 44 , 3–37. [ Google Scholar ] [ CrossRef ]
- Kaplan, A.M.; Haenlein, M. Users of the world, unite! The challenges and opportunities of Social Media. Bus. Horizons 2010 , 53 , 59–68. [ Google Scholar ] [ CrossRef ]
- Furumo, K. The Impact of Conflict and Conflict Management Style on Deadbeats and Deserters in Virtual Teams. In Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008), Waikoloa, HI, USA, 7–10 June 2008; p. 445. [ Google Scholar ] [ CrossRef ]
- Chiravuri, A.; Nazareth, D.; Ramamurthy, K. Cognitive Conflict and Consensus Generation in Virtual Teams During Knowledge Capture: Comparative Effectiveness of Techniques. J. Manag. Inf. Syst. 2011 , 28 , 311–350. [ Google Scholar ] [ CrossRef ]
- Wakefield, R.L.; Leidner, D.E.; Garrison, G. Research Note—A Model of Conflict, Leadership, and Performance in Virtual Teams. Inf. Syst. Res. 2008 , 19 , 434–455. [ Google Scholar ] [ CrossRef ]
- Hinds, P.J.; Mortensen, M. Understanding Conflict in Geographically Distributed Teams: The Moderating Effects of Shared Identity, Shared Context, and Spontaneous Communication. Organ. Sci. 2005 , 16 , 290–307. [ Google Scholar ] [ CrossRef ]
- Kirkman, B.L.; Mathieu, J.E. The Dimensions and Antecedents of Team Virtuality. J. Manag. 2005 , 31 , 700–718. [ Google Scholar ] [ CrossRef ]
- Kramer, W.S.; Shuf, M.L. The world is not flat: Examining the interactive multidimensionality of culture and virtuality in teams. Hum. Resour. Manag. Rev. 2017 , 27 , 604–620. [ Google Scholar ] [ CrossRef ]
- Alves, M.P.; Dimas, I.D.; Lourenço, P.R.; Rebelo, T.; Peñarroja, V.; Gamero, N. Can virtuality be protective of team trust? Conflict and effectiveness in hybrid teams. Behav. Inf. Technol. 2022 , 1–18. [ Google Scholar ] [ CrossRef ]
- Chudoba, K.M.; Wynn, E.; Lu, M.; Watson-Manheim, M.B. How virtual are we? Measuring virtuality and understanding its impact in a global organization. Inf. Syst. J. 2005 , 15 , 279–306. [ Google Scholar ] [ CrossRef ]
- Lü, M.; Watson-Manheim, M.B.; Chudoba, K.M.; Wynn, E. Virtuality and Team Performance: Understanding the Impact of Variety of Practices. J. Glob. Inf. Technol. Manag. 2006 , 9 , 4–23. [ Google Scholar ] [ CrossRef ]
- O’Leary, M.B.; Cummings, J.N. The Spatial, Temporal, and Configurational Characteristics of Geographic Dispersion in Teams. MIS Q. 2007 , 31 , 433–452. [ Google Scholar ] [ CrossRef ]
- Espevik, R.; Johnsen, B.H.; Eid, J.; Thayer, J.F. Shared Mental Models and Operational Effectiveness: Effects on Performance and Team Processes in Submarine Attack Teams. Mil. Psychol. 2006 , 18 , S23–S36. [ Google Scholar ] [ CrossRef ]
- Marlow, S.; Lacerenza, C.N.; Salas, E. Communication in virtual teams: A conceptual framework and research agenda. Hum. Resour. Manag. Rev. 2017 , 27 , 575–589. [ Google Scholar ] [ CrossRef ]
- Olson, G.M.; Olson, J.S. Distance Matters. Hum. Comput. Interact. 2000 , 15 , 139–178. [ Google Scholar ] [ CrossRef ]
- Mello, A.S.; Ruckes, M.E. Team Composition*. J. Bus. 2006 , 79 , 1019–1039. [ Google Scholar ] [ CrossRef ]
- Cortellazzo, L.; Bruni, E.; Zampieri, R. The Role of Leadership in a Digitalized World: A Review. Front. Psychol. 2019 , 10 , 1938. [ Google Scholar ] [ CrossRef ] [ PubMed ]
- Op ‘t Roodt, H.; Krug, H.; Otto, K. Subgroup Formation in Diverse Virtual Teams: The Moderating Role of Identity Leadership. Front. Psychol. 2021 , 12 , 722650. [ Google Scholar ] [ CrossRef ] [ PubMed ]
- Hajro, A.; Gibson, C.B.; Pudelko, M. Knowledge Exchange Processes in Multicultural Teams: Linking Organizational Diversity Climates to Teams’ Effectiveness. Acad. Manag. J. 2017 , 60 , 345–372. [ Google Scholar ] [ CrossRef ]
- Beirouty, Z.A.; Demirel, A.G. Enrichment of Virtual Teams Management through Communication. Asian J. Soc. Sci. Manag. Technol. 2022 , 4 , 15. [ Google Scholar ]
- Lippert, H.; Dulewicz, V. A profile of high-performing global virtual teams. Team Perform. Manag. Int. J. 2018 , 24 , 169–185. [ Google Scholar ] [ CrossRef ]
- Rivera, M. Team Virtuality and Psychological Safety: An Experiment. Master’s Thesis, University of Central Florida, Orlando, FL, USA, 2022. [ Google Scholar ]
- Hacker, J.V.; Johnson, M.; Saunders, C.; Thayer, A.L. Trust in Virtual Teams: A Multidisciplinary Review and Integration. Australas. J. Inf. Syst. 2019 , 23 . [ Google Scholar ] [ CrossRef ]
- Opdenakker, R.; Cuypers, C. Introduction and Field Problem Concerning Virtual Project Teams. In Effective Virtual Project Teams ; Springer International Publishing: Cham, Switzerland, 2019; pp. 1–15. [ Google Scholar ] [ CrossRef ]
- Figl, K.; Saunders, C. Team Climate and Media Choice in Virtual Teams. AIS Trans. Human-Computer Interact. 2011 , 3 , 189–213. [ Google Scholar ] [ CrossRef ]
- Stephens, K.K.; Rains, S.A. Information and Communication Technology Sequences and Message Repetition in Interpersonal Interaction. Commun. Res. 2011 , 38 , 101–122. [ Google Scholar ] [ CrossRef ]
- Furst-Holloway, S.; Blackburn, R.; Rosen, B. Virtual team effectiveness: A proposed research agenda. Inf. Syst. J. 1999 , 9 , 249–269. [ Google Scholar ] [ CrossRef ]
- De Jong, B.A.; Dirks, K.T.; Gillespie, N. Trust and team performance: A meta-analysis of main effects, moderators, and covariates. J. Appl. Psychol. 2016 , 101 , 1134–1150. [ Google Scholar ] [ CrossRef ] [ PubMed ]
- Hung, Y.-T.; Dennis, A.; Robert, L. Robert, Trust in virtual teams: Towards an integrative model of trust formation. In Proceedings of the 37th Annual Hawaii International Conference on System Sciences, Big Island, HI, USA, 5–8 January 2004; p. 11. [ Google Scholar ] [ CrossRef ]
- Kanawattanachai, P.; Yoo, Y. The Impact of Knowledge Coordination on Virtual Team Performance over Time. MIS Q. 2007 , 31 , 783–808. [ Google Scholar ] [ CrossRef ]
- Lewis, J.D.; Weigert, A. Trust as a Social Reality. Soc. Forces 1985 , 63 , 967. [ Google Scholar ] [ CrossRef ]
- McALLISTER, D.J. Affect- And Cognition-Based Trust As Foundations For Interpersonal Cooperation In Organizations. Acad. Manage. J. 1995 , 38 , 36. [ Google Scholar ] [ CrossRef ] [ Green Version ]
- Robert, L.P. Behavior-Output Control Theory, Trust and Social Loafing in Virtual Teams. Multimodal Technol. Interact. 2020 , 4 , 39. [ Google Scholar ] [ CrossRef ]
- Wang, X.; Wei, X.; Van Wart, M.; McCarthy, A.; Liu, C.; Kim, S.; Ready, D.H. The role of E-leadership in ICT utilization: A project management perspective. Inf. Technol. Manag. 2022 , 1–15. [ Google Scholar ] [ CrossRef ]
- Kohntopp, T.; McCann, J. Leadership in Virtual Organizations: Influence on Workplace Engagement. In The Palgrave Handbook of Workplace Well-Being, S. Dhiman ; Springer International Publishing: Cham, Switzerland, 2020; pp. 1–26. [ Google Scholar ] [ CrossRef ]
- Carte, T.A.; Chidambaram, L.; Becker, A. Emergent Leadership in Self-Managed Virtual Teams. Group Decis. Negot. 2006 , 15 , 323–343. [ Google Scholar ] [ CrossRef ]
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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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- 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
495 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, hybrid teamwork: what we know and where we can go from here, interactive effects of team virtuality and work design on team functioning, 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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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.
Task characteristics | Represent elements of task uncertainty that have been the basis of many studies of organizational structure and process ( ) | ; |
VT communication | Defined as when group members must be able to clearly and explicitly exchange information to effectively support collaboration ( ). | ; ; |
Leadership | Defined as a dynamic process of social problem solving accomplished through generic responses to social problems ( ) | |
Cohesion | Defined as the commitment of each team member to remain united in the pursuit of the team’s goals and to each member’s affective needs ( ). | ; |
Empowerment | Defined as the collective belief in a group that it can be effective, and its role in determining group effectiveness ( ). | |
Trust | Is a crucial factor in forming and maintaining social relationships and is key for cooperative relationships and effective teamwork ( ) | ; ; |
Performance | Is the ability to work at the highest level of effectiveness for an extended period of time. This means delivering quality products on time, within budget, while satisfying stakeholders ( ). | ; ; |
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.
n = 317 | |
% | 100.00% |
Male | 81.07% |
Female | 18.93% |
18–29 | 64.98% |
30–39 | 18.93% |
40–49 | 10.41% |
50–59 | 4.73% |
60 or + | 0.95% |
<1 year | 58.99% |
2–5 years | 28.71% |
6–10 years | 7.57% |
11–15 years | 2.84% |
16 or + years | 1.89% |
Leader | 29.65% |
Member | 70.35% |
Yes | 58.04% |
No | 41.96% |
Yes | 76.34% |
No | 23.66% |
Yes | 65.93% |
No | 34.07% |
Yes | 68.45% |
No | 2.84% |
Maybe | 28.71% |
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.
0.851 | 0.910 | 0.771 | 0.878 | |||||||||||||
0.880 | 0.912 | 0.676 | 0.547 | 0.822 | 0.629 | |||||||||||
0.709 | 0.837 | 0.632 | 0.577 | 0.555 | 0.795 | 0.739 | 0.698 | |||||||||
0.864 | 0.902 | 0.648 | 0.599 | 0.786 | 0.615 | 0.805 | 0.698 | 0.898 | 0.781 | |||||||
0.914 | 0.946 | 0.853 | 0.487 | 0.523 | 0.439 | 0.696 | 0.924 | 0.550 | 0.579 | 0.540 | 0.776 | |||||
0.815 | 0.915 | 0.844 | 0.542 | 0.716 | 0.516 | 0.771 | 0.620 | 0.918 | 0.651 | 0.841 | 0.675 | 0.899 | 0.716 | |||
0.867 | 0.904 | 0.653 | 0.486 | 0.599 | 0.525 | 0.639 | 0.536 | 0.568 | 0.808 | 0.564 | 0.685 | 0.669 | 0.735 | 0.600 | 0.674 |
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.
-value | ||||
H1 Characteristics of the tasks → communication of the members of the virtual team | 0.577 | 13.842 | 0.000 | Yes*** |
H2 Leadership in the members of the virtual teams → Trust | 0.138 | 3.209 | 0.001 | Yes*** |
H3 Cohesion in the members of the virtual teams → Trust | 0.366 | 6.725 | 0.000 | Yes*** |
H4 Empowerment for the members of the virtual teams → Trust | 0.348 | 7.086 | 0.000 | Yes*** |
H5 Communication between virtual workers → Trust | 0.160 | 3.741 | 0.000 | Yes*** |
H6 Trust among virtual workers → Performance of the virtual team | 0.684 | 14.281 | 0.000 | Yes*** |
H7 Communication between virtual workers → Performance of the virtual team | 0.019 | 0.353 | 0.724 | Not supported |
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.
(%) | |
Communication (COM) | 33.3 |
Trust (TRU) | 74.2 |
Performance (PER) | 48.4 |
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.
- Abarca V. M. G., Palos-Sanchez P. R., Rus-Arias E. (2020). Working in virtual teams: a systematic literature review and a bibliometric analysis. IEEE Access 8 168923–168940. 10.1109/access.2020.3023546 [ CrossRef ] [ Google Scholar ]
- Alsharo M., Gregg D., Ramirez R. (2017). Virtual team effectiveness: the role of knowledge sharing and trust. Inf. Manage. 54 479–490. 10.1016/j.im.2016.10.005 [ CrossRef ] [ Google Scholar ]
- Altschuller S., Benbunan-Fich R. (2010). Trust, performance, and the communication process in ad hoc decision-making virtual teams. J. Comput.Mediat. Commun. 16 27–47. 10.1111/j.1083-6101.2010.01529.x [ CrossRef ] [ Google Scholar ]
- Andressen P., Konradt U., Neck C. P. (2012). The relation between self-leadership and transformational leadership: competing models and the moderating role of virtuality. J. Leadersh. Organ. Stud. 19 68–82. 10.1177/1548051811425047 [ CrossRef ] [ Google Scholar ]
- Baard S. K., Rench T. A., Kozlowski S. W. J. (2014). Performance adaptation: a theoretical integration and review. J. Manage. 40 48–99. 10.1177/0149206313488210 [ CrossRef ] [ Google Scholar ]
- Bagozzi R. P., Yi Y. (1988). On the evaluation of structural equation models. J. Acad. Mark. Sci. 16 74–94. [ Google Scholar ]
- Baltes B. B., Dickson M. W., Sherman M. P., Bauer C. C., LaGanke J. S. (2002). Computer-mediated communication and group decision making: a meta-analysis. Organ. Behav. Hum. Decis. Process. 87 156–179. 10.1006/obhd.2001.2961 [ CrossRef ] [ Google Scholar ]
- Balthazard P. A., Waldman D. A., Warren J. E. (2009). Predictors of the emergence of transformational leadership in virtual decision teams. Leadersh. Q. 20 651–663. 10.1016/j.leaqua.2009.06.008 [ CrossRef ] [ Google Scholar ]
- Barclay D., Higgins C., Thompson R. (1995). The partial least squares (PLS) approach to casual modeling: personal computer adoption ans use as an Illustration. Technol. Stud. 2 285–309. [ Google Scholar ]
- Bell M., Robertson D., Weeks M., Yu D. (2002). A virtual team group process. Can. J. Nur. Leadersh. 15 30–33. 10.12927/cjnl.2002.19157 [ PubMed ] [ CrossRef ] [ Google Scholar ]
- Bormann E. G. (1983). “ Symbolic convergence: organizational communication and culture ,” in Communication and Organizations: An Interpretive Approach , eds Putnam L., Pacanowsky M. E., (Thousand Oaks, CA: SAGE Publications; ), 99–122. [ Google Scholar ]
- Bormann E. G. (1996). Symbolic convergence theory and communication in group decision making. Commun. Group Decis. Making 2 81–113. 10.4135/9781452243764.n4 [ CrossRef ] [ Google Scholar ]
- Bormann E. G., Craan J. F., Shields D. C. (1994). In defense of symbolic convergence theory: a look at the theory and its criticisms after two decades. Commun. Theory 4 259–294. 10.1111/j.1468-2885.1994.tb00093.x [ CrossRef ] [ Google Scholar ]
- Bormann E. G., Knutson R. L., Musolf K. (1997). Why do people share fantasies? An empirical investigation of a basic tenet of the symbolic convergence communication theory. Commun. Stud. 48 254–276. 10.1080/10510979709368504 [ CrossRef ] [ Google Scholar ]
- Boudreau M.-C., Gefen D., Straub D. W. (2001). Validation in information systems research: a state-of-the-art assessment. MIS Q. 25 1–16. 10.2307/3250956 [ CrossRef ] [ Google Scholar ]
- Brahm T., Kunze F. (2012). The role of trust climate in virtual teams. J. Manage. Psychol. 27 595–614. 10.1108/02683941211252446 [ CrossRef ] [ Google Scholar ]
- Brett J., Behfar K., Kern M. C. (2006). Managing Multicultural Teams. Brighton, MA: Harvard Business Review. [ PubMed ] [ Google Scholar ]
- Brooks S. K., Webster R. K., Smith L. E., Woodland L., Wessely S., Greenberg N., et al. (2020). The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet 395 912–920. 10.1016/s0140-6736(20)30460-8 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
- Bryant S. M., Albring S. M., Murthy U. (2009). The effects of reward structure, media richness and gender on virtual teams. Int. J. Account. Inf. Syst. 10 190–213. 10.1016/j.accinf.2009.09.002 [ CrossRef ] [ Google Scholar ]
- Burke C. S., Stagl K. C., Klein C., Goodwin G. F., Salas E., Halpin S. M. (2006). What type of leadership behaviors are functional in teams? A meta-analysis. Leadersh. Q. 17 288–307. 10.1016/j.leaqua.2006.02.007 [ CrossRef ] [ Google Scholar ]
- Campion M. A., Medsker G. J., Higgs A. C. (1993). Relations between work group characteristics and effectiveness: implications for designing effective work groups. Pers. Psychol. 46 823–847. 10.1111/j.1744-6570.1993.tb01571.x [ CrossRef ] [ Google Scholar ]
- Chen C., de Rubens G. Z., Xu X., Li J. (2020). Coronavirus comes home? Energy use, home energy management, and the social-psychological factors of COVID-19. Energy Res. Soc. Sci. 68 101688 . 10.1016/j.erss.2020.101688 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
- Chin W. W. (1998). The partial least squares aproach to structural equation modeling . Mod. Methods Bus. Res. 295 , 295–336. [ Google Scholar ]
- Chin W. W. (2010). “ How to write up and report PLS analyses ,” in Handbook of Partial Least Squares , eds Wang H., Henseler J., Vinzi V. E., Chin W. W., (Berlin: Springer; ), 655–690. 10.1007/978-3-540-32827-8_29 [ CrossRef ] [ Google Scholar ]
- Chin W. W., Newsted P. R. (1999). Structural equation modeling analysis with small samples using partial least squares. Stat. Strategies Small Sample Res. 1 307–341. [ Google Scholar ]
- Coppola N. W., Hiltz S. R., Rotter N. G. (2004). Building trust in virtual teams. IEEE Trans. Prof. Commun. 47 95–104. 10.1109/TPC.2004.828203 [ CrossRef ] [ Google Scholar ]
- Cramton C. D., Webber S. S. (2005). Relationships among geographic dispersion, team processes, and effectiveness in software development work teams. J. Bus. Res. 58 758–765. 10.1016/j.jbusres.2003.10.006 [ CrossRef ] [ Google Scholar ]
- Crisp C. B., Jarvenpaa S. L. (2013). Swift trust in global virtual teams. J. Pers. Psychol. 12 45–56. 10.1027/1866-5888/a000075 [ CrossRef ] [ Google Scholar ]
- Cummings J. N., Haas M. R. (2012). So many teams, so little time: time allocation matters in geographically dispersed teams. J. Organ. Behav. 33 316–341. 10.1002/job.777 [ CrossRef ] [ Google Scholar ]
- Daft R. L., Lengel R. H. (1986). Organizational information requirements, media richness and structural design. Manage. Sci. 32 554–571. 10.1287/mnsc.32.5.554 [ CrossRef ] [ Google Scholar ]
- Daft R. L., Macintosh N. B. (1981). A tentative exploration into the amount and equivocality of information processing in organizational work units. Adm. Sci. Q. 26 207–224. 10.2307/2392469 [ CrossRef ] [ Google Scholar ]
- David Strang K. (2011). Leadership substitutes and personality impact on time and quality in virtual new product development projects. Proj. Manage. J. 42 73–90. 10.1002/pmj.20208 [ CrossRef ] [ Google Scholar ]
- Dayan M., Di Benedetto C. A. (2010). The impact of structural and contextual factors on trust formation in product development teams. Ind. Mark. Manage. 39 691–703. 10.1016/j.indmarman.2010.01.001 [ CrossRef ] [ Google Scholar ]
- De Jong B. A., Elfring T. (2010). How does trust affect the performance of ongoing teams? The mediating role of reflexivity, monitoring, and effort. Acad. Manage. J. 53 535–549. 10.5465/amj.2010.51468649 [ CrossRef ] [ Google Scholar ]
- de Ven A. H., Delbecq A. L., Koenig R., Jr. (1976). Determinants of coordination modes within organizations. Am. Soc. Rev. 41 322–338. 10.2307/2094477 [ CrossRef ] [ Google Scholar ]
- Dennis A. R., Kinney S. T. (1998). Testing media richness theory in the new media: the effects of cues, feedback, and task equivocality. Inf. Syst. Res. 9 256–274. 10.1287/isre.9.3.256 [ CrossRef ] [ Google Scholar ]
- Duarte D. L., Snyder N. T. (2006). Mastering Virtual Teams: Strategies, Tools, and Techniques that Succeed. Hoboken, NJ: John Wiley & Sons. [ Google Scholar ]
- Dulebohn J. H., Hoch J. E. (2017). Virtual teams in organizations. Hum. Resour. Manage. Rev. 27 569–574. 10.1016/j.hrmr.2016.12.004 [ CrossRef ] [ Google Scholar ]
- Duncan R. B. (1972). Characteristics of organizational environments and perceived environmental uncertainty. Adm. Sci. Q. 17 313–327. 10.2307/2392145 [ CrossRef ] [ Google Scholar ]
- Ebrahim N. A., Ahmed S., Taha Z. (2009). Virtual teams: a literature review. Aust. J. Basic Appl. Sci. 3 2653–2669. [ Google Scholar ]
- Evans C. R., Dion K. L. (1991). Group cohesion and performance: a meta-analysis. Small Group Res. 22 175–186. 10.1177/1046496491222002 [ CrossRef ] [ Google Scholar ]
- Fornell C., Larcker D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18 39–50. 10.2307/3151312 [ CrossRef ] [ Google Scholar ]
- Fuller M. A., Hardin A. M., Davison R. M. (2006). Efficacy in technology-mediated distributed teams. J. Manage. Inf. Syst. 23 209–235. 10.2753/mis0742-1222230308 [ CrossRef ] [ Google Scholar ]
- Furumo K. (2009). The impact of conflict and conflict management style on deadbeats and deserters in virtual teams. J. Comput. Inf. Syst. 49 66–73. [ Google Scholar ]
- Galbraith J. R. (1973). Designing Complex Organizations. Boston, MA: Addison-Wesley Longman Publishing Co., Inc. [ Google Scholar ]
- Garrison G., Wakefield R. L., Xu X., Kim S. H. (2010). Globally distributed teams: the effect of diversity on trust, cohesion and individual performance. ACM SIGMIS Database Database Adv. Inf. Syst. 41 27–48. 10.1145/1851175.1851178 [ CrossRef ] [ Google Scholar ]
- Geber B. (1995). Virtual teams. Training 32 36–40. [ Google Scholar ]
- Gilson L. L., Maynard M. T., Young N. C. J., Vartiainen M., Hakonen M. (2015). Virtual teams research: 10 Years, 10 themes, and 10 opportunities. J. Manage. 41 1313–1337. 10.1177/0149206314559946 [ CrossRef ] [ Google Scholar ]
- Glückler J., Schrott G. (2007). Leadership and performance in virtual teams: exploring brokerage in electronic communication. Int. J. E-Collaboration (IJeC) 3 31–52. 10.4018/jec.2007070103 [ CrossRef ] [ Google Scholar ]
- Goh S., Wasko M. (2012). The effects of leader-member exchange on member performance in virtual world teams. J. Assoc. Inf. Syst. 13 861–885. 10.17705/1jais.00308 [ CrossRef ] [ Google Scholar ]
- Gondal A. M., Khan A. (2008). Impact of team empowerment on team performance: case of the telecommunications industry in Islamabad. Int. Rev. Bus. Res. Papers 4 138–146. [ Google Scholar ]
- Griffin E. (1997). Groupthink. A First Look at Communication Theory. New York, NY: McGraw-Hill Education. [ Google Scholar ]
- Guzzo R. A., Yost P. R., Campbell R. J., Shea G. P. (1993). Potency in groups: articulating a construct. Br. J. Soc. Psychol. 32 87–106. 10.1111/j.2044-8309.1993.tb00987.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
- Hair J. F., Ringle C. M., Sarstedt M. (2011). PLS-SEM: indeed a silver bullet. J. Mark. Theory Pract. 19 139–152. 10.2753/mtp1069-6679190202 [ CrossRef ] [ Google Scholar ]
- Hair J. F., Ringle C. M., Sarstedt M. (2013). Partial least squares structural equation modeling: rigorous applications, better results and higher acceptance. Long Range Plan. 46 1–12. 10.1016/j.lrp.2013.01.001 [ CrossRef ] [ Google Scholar ]
- Han H.-J., Hiltz S. R., Fjermestad J., Wang Y. (2011). Does medium matter? A comparison of initial meeting modes for virtual teams. IEEE Trans. Prof. Commun. 54 376–391. 10.1109/tpc.2011.2175759 [ CrossRef ] [ Google Scholar ]
- Henderson L. S. (2008). The impact of project managers’ communication competencies: validation and extension of a research model for virtuality, satisfaction, and productivity on project teams. Proj. Manage. J. 39 48–59. 10.1002/pmj.20044 [ CrossRef ] [ Google Scholar ]
- Henseler J. (2017). Bridging design and behavioral research with variance-based structural equation modeling. J. Adv. 46 178–192. 10.1080/00913367.2017.1281780 [ CrossRef ] [ Google Scholar ]
- Henseler J., Hubona G., Ray P. A. (2016). Using PLS path modeling in new technology research: updated guidelines. Ind. Manage. Data Syst. 116 2–20. 10.1108/imds-09-2015-0382 [ CrossRef ] [ Google Scholar ]
- Henttonen K., Blomqvist K. (2005). Managing distance in a global virtual team: the evolution of trust through technology-mediated relational communication. Strategic Change 14 107–119. 10.1002/jsc.714 [ CrossRef ] [ Google Scholar ]
- Hertel G., Geister S., Konradt U. (2005). Managing virtual teams: a review of current empirical research. Hum. Resour. Manage. Rev. 15 69–95. 10.1016/j.hrmr.2005.01.002 [ CrossRef ] [ Google Scholar ]
- Hoch J. E., Kozlowski S. W. J. (2014). Leading virtual teams: hierarchical leadership, structural supports, and shared team leadership. J. Appl. Psychol. 99 390–403. 10.1037/a0030264 [ PubMed ] [ CrossRef ] [ Google Scholar ]
- Hogg M. A. (1987). “ Social identity and group cohesiveness ,” in Rediscovering the Social Group: A Self-Categorization Theory , ed. Turner J., (New York, NY: Basil Blackwell; ), 89–116. [ Google Scholar ]
- Hogg M. A., Tindale R. S. (2001). Group Processes. Malden, MA: Blackwell. [ Google Scholar ]
- Hu L., Bentler P. M. (1998). Fit indices in covariance structure modeling: sensitivity to underparameterized model misspecification. Psychol. Methods 3 : 424 . 10.1037/1082-989x.3.4.424 [ CrossRef ] [ Google Scholar ]
- Huang R., Kahai S., Jestice R. (2010). The contingent effects of leadership on team collaboration in virtual teams. Comput. Hum. Behav. 26 1098–1110. 10.1016/j.chb.2010.03.014 [ CrossRef ] [ Google Scholar ]
- Jarrahi M. H., Sawyer S. (2013). Social technologies, informal knowledge practices, and the enterprise. J. Organ. Comput. Electron. Commer. 23 110–137. 10.1080/10919392.2013.748613 [ CrossRef ] [ Google Scholar ]
- Joshi A., Lazarova M. B., Liao H. (2009). Getting everyone on board: the role of inspirational leadership in geographically dispersed teams. Organ. Sci. 20 240–252. 10.1287/orsc.1080.0383 [ CrossRef ] [ Google Scholar ]
- Kerr S., Jermier J. M. (1978). Substitutes for leadership: their meaning and measurement. Organ. Behav. Hum. Perf. 22 375–403. 10.1016/0030-5073(78)90023-5 [ CrossRef ] [ Google Scholar ]
- Kirkman B. L., Cordery J. L., Mathieu J., Rosen B., Kukenberger M. (2013). Global organizational communities of practice: the effects of nationality diversity, psychological safety, and media richness on community performance. Hum. Relations 66 333–362. 10.1177/0018726712464076 [ CrossRef ] [ Google Scholar ]
- Kirkman B. L., Rosen B., Tesluk P. E., Gibson C. B. (2004). The impact of team empowerment on virtual team performance: the moderating role of face-to-face interaction. Acad. Manage. J. 47 175–192. 10.5465/20159571 [ CrossRef ] [ Google Scholar ]
- Kock N., Lynn G. S. (2012). Electronic media variety and virtual team performance: the mediating role of task complexity coping mechanisms. IEEE Trans. Prof. Commun. 55 325–344. 10.1109/TPC.2012.2208393 [ CrossRef ] [ Google Scholar ]
- Konradt U., Hoch J. E. (2007). A work roles and leadership functions of managers in virtual teams. Int. J. E-Collaboration (IJeC) 3 16–35. 10.4018/jec.2007040102 [ CrossRef ] [ Google Scholar ]
- Kort E. D. (2008). What, after all, is leadership?‘Leadership’and plural action. Leadersh. Q. 19 409–425. 10.1016/j.leaqua.2008.05.003 [ CrossRef ] [ Google Scholar ]
- Lin C., Standing C., Liu Y.-C. (2008). A model to develop effective virtual teams. Decis. Support Syst. 45 1031–1045. 10.1016/j.dss.2008.04.002 [ CrossRef ] [ Google Scholar ]
- Lott A. J., Lott B. E. (1965). Group cohesiveness as interpersonal attraction: a review of relationships with antecedent and consequent variables. Psychol. Bull. 64 : 259 . 10.1037/h0022386 [ PubMed ] [ CrossRef ] [ Google Scholar ]
- Lowry P. B., Roberts T. L., Romano N. C., Jr., Cheney P. D., Hightower R. T. (2006). The impact of group size and social presence on small-group communication: does computer-mediated communication make a difference? Small Group Res. 37 631–661. 10.1177/1046496406294322 [ CrossRef ] [ Google Scholar ]
- Lowry P. B., Zhang D., Zhou L., Fu X. (2010). Effects of culture, social presence, and group composition on trust in technology-supported decision-making groups. Inf. Syst. J. 20 297–315. 10.1111/j.1365-2575.2009.00334.x [ CrossRef ] [ Google Scholar ]
- Lu L. (2015). Building trust and cohesion in virtual teams: the developmental approach. J. Organ. Eff. People Perf. 2 55–72. 10.1108/JOEPP-11-2014-0068 [ CrossRef ] [ Google Scholar ]
- Makoul G., Curry R. H. (2007). The value of assessing and addressing communication skills. Jama 298 1057–1059. 10.1001/jama.298.9.1057 [ PubMed ] [ CrossRef ] [ Google Scholar ]
- Martinez-Cañas R., Ruiz-Palomino P., Linuesa-Langreo J., Blázquez-Resino J. J. (2016). Consumer participation in co-creation: an enlightening model of causes and effects based on ethical values and transcendent motives. Front. Psychol. 7 : 793 . 10.3389/fpsyg.2016.00793 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
- Martins L. L., Gilson L. L., Maynard M. T. (2004). Virtual teams: what do we know and where do we go from here? J. Manage. 30 805–835. 10.1016/j.jm.2004.05.002 [ CrossRef ] [ Google Scholar ]
- Maynard M. T., Mathieu J. E., Rapp T. L., Gilson L. L. (2012). Something(s) old and something(s) new: modeling drivers of global virtual team effectiveness. J. Organ. Behav. 33 342–365. 10.1002/job.1772 [ CrossRef ] [ Google Scholar ]
- McBer and Company. (1980). Trainer’s Guide. Boston, MA: McBer and Company. [ Google Scholar ]
- Mohr L. B. (1971). Organizational technology and organizational structure. Adm. Sci. Q. 16 444–459. 10.2307/2391764 [ CrossRef ] [ Google Scholar ]
- Montoya-Weiss M. M., Massey A. P., Song M. (2001). Getting it together: temporal coordination and conflict management in global virtual teams. Acad. Manage. J. 44 1251–1262. 10.2307/3069399 [ CrossRef ] [ Google Scholar ]
- Palos P. R., Correia M. B. (2017). La actitud de los recursos humanos de las organizaciones ante la complejidad de las aplicaciones SaaS. Dos Algarves Multidiscip. J. 28 87–103. 10.18089/damej.2016.28.1.6 [ CrossRef ] [ Google Scholar ]
- Palos-Sanchez P. R. (2017). El cambio de las relaciones con el cliente a través de la adopción de APPS: estudio de las variables de influencia en M-Commerce. Rev. Espacios 38 : 38 . [ Google Scholar ]
- Peñarroja V., Orengo V., Zornoza A., Hernández A. (2013). The effects of virtuality level on task-related collaborative behaviors: the mediating role of team trust. Comput. Hum. Behav. 29 967–974. 10.1016/j.chb.2012.12.020 [ CrossRef ] [ Google Scholar ]
- Perrow C. (1967). A framework for the comparative analysis of organizations. Am. Soc. Rev. 32 194–208. 10.2307/2091811 [ CrossRef ] [ Google Scholar ]
- Piccoli G., Powell A., Ives B. (2004). Virtual teams: team control structure, work processes, and team effectiveness. Inf. Technol. People 17 359–379. 10.1108/09593840410570258 [ CrossRef ] [ Google Scholar ]
- Pitagorsky G. (2007). “ Managing virtual teams for high performance ,” in Paper Presented at PMI§Global Congress , (North America, Atlanta, GA: Project Management Institute; ). [ Google Scholar ]
- Powell A., Piccoli G., Ives B. (2004). Virtual teams: a review of current literature and directions for future research. SIGMIS Database 35 6–36. 10.1145/968464.968467 [ CrossRef ] [ Google Scholar ]
- Pridmore J., Phillips-Wren G. (2011). Assessing decision making quality in face-to-face teams versus virtual teams in a virtual world. J. Decis. Syst. 20 283–308. 10.3166/jds.20.283-308 [ CrossRef ] [ Google Scholar ]
- Purvanova R. K., Bono J. E. (2009). Transformational leadership in context: Face-to-face and virtual teams. Leadersh. Q. 20 343–357. 10.1016/j.leaqua.2009.03.004 [ CrossRef ] [ Google Scholar ]
- Rapp A., Ahearne M., Mathieu J., Rapp T. (2010). Managing sales teams in a virtual environment. Int. J. Res. Mark. 27 213–224. [ Google Scholar ]
- Rashid M., Dar J. (1994). Current managerial styles & effective managers. Manage. Serv. 38 16–17. [ Google Scholar ]
- Reinartz W., Haenlein M., Henseler J. (2009). An empirical comparison of the efficacy of covariance-based and variance-based SEM. Int. J. Res. Mark. 26 332–344. 10.1016/j.ijresmar.2009.08.001 [ CrossRef ] [ Google Scholar ]
- Ribes-Giner G., Perelló-Marin M. R., Pantoja-Diaz O. (2017). Revisión sistemática de literatura de las variables clave del proceso de co-creación en las instituciones de educación superior. Tec. Empre. 11 41–53. 10.18845/te.v11i3.3365 [ CrossRef ] [ Google Scholar ]
- Rico R., Cohen S. G. (2005). Effects of task interdependence and type of communication on performance. J. Manage. Psychol. 20 261–274. 10.1108/02683940510589046 [ CrossRef ] [ Google Scholar ]
- Saldaña Ramos J. (2010). VTManager: Un Marco Metodológico Para la Mejora de la Gestión de Los Equipos de Desarrollo Software Global. Madrid: Universidad Carlos III de Madrid. [ Google Scholar ]
- Salisbury W. D., Carte T. A., Chidambaram L. (2006). Cohesion in virtual teams: validating the perceived cohesion scale in a distributed setting. SIGMIS Database 37 147–155. 10.1145/1161345.1161362 [ CrossRef ] [ Google Scholar ]
- Sánchez P. R. P. (2017). Drivers and barriers of the cloud computing in SMEs: the position of the European union. Harv. Deusto Bus. Res. 6 116–132. [ Google Scholar ]
- Sarker S., Sarker S., Schneider C. (2009). Seeing remote team members as leaders: a study of US-Scandinavian teams. IEEE Trans. Prof. Commun. 52 75–94. 10.1109/TPC.2008.2007871 [ CrossRef ] [ Google Scholar ]
- Schepers J., de Jong A., de Ruyter K., Wetzels M. (2011). Fields of gold: perceived efficacy in virtual teams of field service employees. J. Service Res. 14 372–389. 10.1177/1094670511412354 [ CrossRef ] [ Google Scholar ]
- Schweitzer L., Duxbury L. (2010). Conceptualizing and measuring the virtuality of teams. Inf. Syst. J. 20 267–295. 10.1111/j.1365-2575.2009.00326.x [ CrossRef ] [ Google Scholar ]
- Shuffler M. L., Wiese C. W., Salas E., Burke C. S. (2010). Leading one another across time and space: exploring shared leadership functions in virtual teams. Rev.Psicolog Trabajo Las Organ. 26 3–17. 10.5093/tr2010v26n1a1 [ CrossRef ] [ Google Scholar ]
- Simons T. L., Peterson R. S. (2000). Task conflict and relationship conflict in top management teams: the pivotal role of intragroup trust. J. Appl. Psychol. 85 : 102 . 10.1037/0021-9010.85.1.102 [ PubMed ] [ CrossRef ] [ Google Scholar ]
- Spector T. (2006). Does the sustainability movement sustain a sustainable design ethic for architecture? Environ. Ethics 28 265–283. 10.5840/enviroethics200628317 [ CrossRef ] [ Google Scholar ]
- Subramanyam V. (2013). Team cohesion between national youth and junior volley ball players: a comparative analysis . Int. J. Sports Sci. Fitness 3 , 250–258. [ Google Scholar ]
- Tan C. K.\, Ramayah T., Teoh A. P., Cheah J.-H. (2019). Factors influencing virtual team performance in Malaysia . Kybernetes 48 , 2065–2092. 10.1108/K-01-2018-0031 [ CrossRef ] [ Google Scholar ]
- Velicia-Martin F., Cabrera-Sanchez J.-P., Gil-Cordero E., Palos-Sanchez P. R. (2021). Researching COVID-19 tracing app acceptance: incorporating theory from the technological acceptance model. PeerJ Comput. Sci. 7 : e316 . 10.7717/peerj-cs.316 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
- Warkentin M., Beranek P. M. (1999). Training to improve virtual team communication. Inf. Syst. J. 9 271–289. 10.1046/j.1365-2575.1999.00065.x [ CrossRef ] [ Google Scholar ]
- Wei L. H., Thurasamy R., Popa S. (2018). Managing virtual teams for open innovation in Global Business Services industry. Manage. Decis. 56 1285–1305. 10.1108/MD-08-2017-0766 [ CrossRef ] [ Google Scholar ]
- Werts C. E., Linn R. L., Jöreskog K. G. (1974). “ Quantifying unmeasured variables ,” in Measurement in the Social Sciences , ed. Blalock H. M., (Chicago: Aldine Publishing Co; ), 270–292. 10.4324/9781351329088-11 [ CrossRef ] [ Google Scholar ]
- Whitford T., Moss S. A. (2009). Transformational leadership in distributed work groups: the moderating role of follower regulatory focus and goal orientation. Commun. Res. 36 810–837. 10.1177/0093650209346800 [ CrossRef ] [ Google Scholar ]
- Zúñiga Ramirez C., Solano Cordero J., Bolaños Garita R. (2016). Quantic trends in knowledge-based companies: a case analysis of a Costa Rican experience. Tec. Empresarial 10 29–40. 10.18845/te.v10i3.2938 [ CrossRef ] [ Google Scholar ]
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.
Ackerman MS (2000) The intellectual challenge of CSCW: the gap between social requirements and technical feasibility. Hum Comput Interact 15(2–3):179–203
Google Scholar
Ågerfalk PJ, Fitzgerald B, Holmstrom Olsson H, Lings B, Lundell B, Ó Conchúir E (2005) A framework for considering opportunities and threats in distributed software development. In: Proceedings of the of DiSD’05. Austrian Computer Society, pp 47–61
Alder GS, Noel TW, Ambrose ML (2006) Clarifying the effects of internet monitoring on job attitudes: the mediating role of employee trust. Inf Manag 43(7):894–903
Allen TJ (1984) Managing the flow of technology: technology transfer and the dissemination of technological information within the R&D organization. MIT Press Books 1, London
Alsharo M, Gregg D, Ramirez R (2017) Virtual team effectiveness: the role of knowledge sharing and trust. Inf Manag 54(4):479–490
Apple Inc (2017) Use FaceTime with your iPhone, iPad, or iPod touch. https://support.apple.com/en-us/HT204380
Ardissono L, Bosio G (2012) Context-dependent awareness support in open collaboration environments. UMUAI 22(3):223–254
Armstrong DJ, Cole P (1995) Managing distances and differences in geographically distributed work groups. In: Jackson SE, Ruderman MN (eds) Diversity in work teams: research paradigms for a changing workplace. American Psychological Association, pp 187–215. https://doi.org/10.1037/10189-007
Barczak G, Lassk F, Mulki J (2010) Antecedents of team creativity: an examination of team emotional intelligence, team trust and collaborative culture. Creat Innov Manag 19(4):332–345
Batarseh FS, Usher JM, Daspit JJ (2017) Collaboration capability in virtual teams: examining the influence on diversity and innovation. Int J Innov Manag 21(04):1750034
Battin RD, Crocker R, Kreidler J, Subramanian K (2001) Leveraging resources in global software development. IEEE Softw 18(2):70–77
Bell BS, Kozlowski W (2002) Goal orientation and ability: interactive effects on self-efficacy, performance, and knowledge. J Appl Psychol 87(3):497
Berry GR (2011) Enhancing effectiveness on virtual teams: understanding why traditional team skills are insufficient. J Bus Commun (1973) 48(2):186–206
Bjørn P, Ngwenyama O (2009) Virtual team collaboration: building shared meaning, resolving breakdowns and creating translucence. Inf Syst J 19(3):227–253
Bjørn P, Esbensen M, Jensen RE, Matthiesen S (2014) Does distance still matter? Revisiting the CSCW fundamentals on distributed collaboration. TOCHI 21(5):27
Blaskovich JL (2008) Exploring the effect of distance: an experimental investigation of virtual collaboration, social loafing, and group decisions. J Inf Syst 22(1):27–46
Bly SA, Harrison SR, Irwin S (1993) Media spaces: bringing people together in a video, audio, and computing environment. Commun ACM 36(1):28–46
Bodemer D, Dehler J (2011) Group awareness in CSCL environments. Comput Hum Behav 27(3):1043–1045
Boland D, Fitzgerald B (2004) Transitioning from a co-located to a globally-distributed software development team: a case study at Analog Devices Inc. In: Proceedings of the international workshop on global software development at ICSE’04. IET, pp 4–7
Bos N, Olson J, Gergle D, Olson G, Wright Z (2002) Effects of four computer—mediated communications channels on trust development. In: Proceedings the of CHI’02. ACM, New York, pp 135–140
Bradner E, Mark G (2002) Why distance matters: effects on cooperation, persuasion and deception. In: Proceedings of CSCW’02. ACM, New York, CSCW’02, pp 226–235
Brannen MY, Salk JE (2000) Partnering across borders: negotiating organizational culture in a German–Japanese joint venture. Hum Relat 53(4):451–487
Breuer C, Hüffmeier J, Hertel G (2016) Does trust matter more in virtual teams? A meta-analysis of trust and team effectiveness considering virtuality and documentation as moderators. J Appl Psychol 101(8):1151
Brewer MB (1979) In-group bias in the minimal intergroup situation: a cognitive-motivational analysis. Psychol Bull 86(2):307
Buder J (2011) Group awareness tools for learning: current and future directions. Comput Hum Behav 27(3):1114–1117
Budgen D, Burn AJ, Brereton OP, Kitchenham BA, Pretorius R (2011) Empirical evidence about the UML: a systematic literature review. Softw Pract Exp 41(4):363–392
Burke K, Aytes K, Chidambaram L, Johnson JJ (1999) A study of partially distributed work groups: the impact of media, location, and time on perceptions and performance. Small Group Res 30(4):453–490
Buvik MP, Tvedt SD (2017) The influence of project commitment and team commitment on the relationship between trust and knowledge sharing in project teams. Proj Manag J 48(2):5–21
Calefato F, Lanubile F (2017) Establishing personal trust-based connections in distributed teams. Internet Technol Lett 1:e6
Calefato F, Lanubile F, Novielli N (2017) A preliminary analysis on the effects of propensity to trust in distributed software development. In: Proceedings of ICGSE’17. IEEE, New York, pp 56–60
Carmel E, Agarwal R (2001) Tactical approaches for alleviating distance in global software development. IEEE Softw 18(2):22–29
Carte T, Chidambaram L (2004) A capabilities-based theory of technology deployment in diverse teams: leapfrogging the pitfalls of diversity and leveraging its potential with collaborative technology. J Assoc Inf Syst 5(11):4
Casey V, Richardson I (2004) Practical experience of virtual team software development. https://ulir.ul.ie/bitstream/handle/10344/2149/2004_Casey.pdf?sequence=2
Chae SW (2016) Perceived proximity and trust network on creative performance in virtual collaboration environment. Proc Comput Sci 91(Itqm):807–812
Charlier SD, Stewart GL, Greco LM, Reeves CJ (2016) Emergent leadership in virtual teams: a multilevel investigation of individual communication and team dispersion antecedents. Leadersh Q 27(5):745–764
Cheng X, Fu S, Druckenmiller D (2016) Trust development in globally distributed collaboration: a case of us and chinese mixed teams. J Manag Inf Syst 33(4):978–1007
Cheng X, Fu S, Sun J, Han Y, Shen J, Zarifis A (2016) Investigating individual trust in semi-virtual collaboration of multicultural and unicultural teams. Comput Hum Behav 62:267–276
Cheng X, Yin G, Azadegan A, Kolfschoten G (2016) Trust evolvement in hybrid team collaboration: a longitudinal case study. Group Decis Negot 25(2):267–288
Chidambaram L, Tung LL (2005) Is out of sight, out of mind? An empirical study of social loafing in technology-supported groups. Inf Syst Res 16(2):149–168
Chinowsky PS, Taylor JE (2011) Distance matters: a social network analysis of geographic dispersion in engineering organizations. In: Proceedings of EPOC’11
Cho J (2006) The mechanism of trust and distrust formation and their relational outcomes. J Retail 82(1):25–35
Choi OK, Cho E (2019) The mechanism of trust affecting collaboration in virtual teams and the moderating roles of the culture of autonomy and task complexity. Comput Hum Behav 91:305–315
Clark HH, Brennan SE (1991) Grounding in communication. In: Perspectives on socially shared cognition. American Psychological Association, Washington, DC, pp 127–149
Colquitt JA, Scott BA, LePine JA (2007) Trust, trustworthiness, and trust propensity: a meta-analytic test of their unique relationships with risk taking and job performance. J Appl Psychol 92(4):909
Cooper CD, Kurland NB (2002) Telecommuting, professional isolation, and employee development in public and private organizations. J Organ Behav 23(4):511–532
Cramton CD (2001) The mutual knowledge problem and its consequences for dispersed collaboration. Organ Sci 12(3):346–371
Cramton CD, Hinds PJ (2004) Subgroup dynamics in internationally distributed teams: ethnocentrism or cross-national learning? Res Organ Behav 26:231–263
Crisp CB, Jarvenpaa SL (2013) Swift trust in global virtual teams: trusting beliefs and normative actions. J Pers Psychol 12(1):45
Cummings JN (2011) Geography is alive and well in virtual teams. Commun ACM 54(8):24–26
Cummings JN, Kiesler S (2005) Collaborative research across disciplinary and organizational boundaries. Soc Stud Sci 35(5):703–722
Cummings JN, Kiesler S (2007) Coordination costs and project outcomes in multi-university collaborations. RP 36(10):1620–1634
Cummings JN, Kiesler S (2008) Who collaborates successfully? Prior experience reduces collaboration barriers in distributed interdisciplinary research. In: Proceedings of CSCW’08. ACM, New York, pp 437–446
Cummings L, Bromiley P (1996) The organizational trust inventory (OTI): development and validation. In: Kramer RM, Tyler TR (eds) Trust in organizations: frontiers of theory and research. Sage, Thousand Oaks, pp 302–330
Cundill G, Harvey B, Tebboth M, Cochrane L, Currie-Alder B, Vincent K, Lawn J, Nicholls RJ, Scodanibbio L, Prakash A et al (2019) Large-scale transdisciplinary collaboration for adaptation research: challenges and insights. Glob Chall 3(4):1700132
Curtis B, Krasner H, Iscoe N (1988) A field study of the software design process for large systems. Commun ACM 31(11):1268–1287
Dahlin KB, Weingart LR, Hinds PJ (2005) Team diversity and information use. Acad Manag J 48(6):1107–1123
Damian DE, Zowghi D (2002) The impact of stakeholders’ geographical distribution on managing requirements in a multi-site organization. In: Proceedings of RE’02. IEEE, New York, pp 319–328
Darics E (2014) The blurring boundaries between synchronicity and asynchronicity: new communicative situations in work-related instant messaging. Int J Bus Commun 51(4):337–358
De Jong BA, Dirks KT, Gillespie N (2016) Trust and team performance: a meta-analysis of main effects, moderators, and covariates. J Appl Psychol 101(8):1134
Dennis AR, Fuller RM, Valacich JS (2008) Media, tasks, and communication processes: a theory of media synchronicity. MIS Q 32(3):575–600
Desanctis G, Monge P (1999) Introduction to the special issue: communication processes for virtual organizations. Organ Sci 10(6):693–703
Dourish P, Bellotti V (1992) Awareness and coordination in shared workspaces. In: Proceedings of CSCW’92. ACM, New York, pp 107–114
Duarte DL, Snyder NT (2006) Mastering virtual teams: strategies, tools, and techniques that succeed. Wiley, Berlin
Dubé L, Robey D (2009) Surviving the paradoxes of virtual teamwork. ISJ 19(1):3–30
Dvir T, Eden D, Avolio BJ, Shamir B (2002) Impact of transformational leadership on follower development and performance: a field experiment. Acad Manag J 45(4):735–744
Edwards HK, Sridhar V (2005) Analysis of software requirements engineering exercises in a global virtual team setup. J Glob Inf Manag (JGIM) 13(2):21–41
Eisenberg J, Krishnan A (2018) Addressing virtual work challenges: learning from the field. Organ Manag J 15(2):78–94
Eisenberg J, Mattarelli E (2017) Building bridges in global virtual teams: the role of multicultural brokers in overcoming the negative effects of identity threats on knowledge sharing across subgroups. J Int Manag 23(4):399–411
Eisenberg J, Post C, DiTomaso N (2019) Team dispersion and performance: the role of team communication and transformational leadership. Small Group Res 50(3):348–380
Elron E (1997) Top management teams within multinational corporations: effects of cultural heterogeneity. Leadersh Q 8(4):393–412
Erickson T, Smith DN, Kellogg WA, Laff M, Richards JT, Bradner E (1999) Socially translucent systems: social proxies, persistent conversation, and the design of “babble”. In: Proceedings of CHI’99. ACM, New York, pp 72–79
Esbensen M, Bjørn P (2014) Routine and standardization in global software development. In: Proceedings of GROUP’14. ACM, New York, pp 12–23
Espinosa JA, Carmel E (2004) The effect of time separation on coordination costs in global software teams: a dyad model. In: Proceedings of HICSS’04. IEEE, New York, p 10
Espinosa JA, Pickering C (2006) The effect of time separation on coordination processes and outcomes: a case study. In: Proceedings of HICSS’06, vol 1. IEEE, New York, pp 25b–25b
Espinosa JA, Cummings JN, Pickering C (2011) Time separation, coordination, and performance in technical teams. IEEE Trans Eng Manag 59(1):91–103
Ferrell JZ, Herb KC (2012) Improving communication in virtual teams, pp 1–7. https://www.siop.org/Research-Publications/SIOP-White-Papers
Finholt T, Sproull L, Kiesler S (1990) Communication and performance in ad hoc task groups. In: Galegher J, Kraut RE (eds) Intellectual teamwork: social and technological foundations of cooperative work. Psychology Press, New York, pp 291–325
Finholt TA, Olson GM (1997) From laboratories to collaboratories: a new organizational form for scientific collaboration. Psychol Sci 8(1):28–36
Fjermestad J (2004) An analysis of communication mode in group support systems research. Decis Support Syst 37(2):239–263
Gajendran RS, Harrison DA, Delaney-Klinger K (2015) Are telecommuters remotely good citizens? Unpacking telecommuting’s effects on performance via i-deals and job resources. Pers Psychol 68(2):353–393
Gaver WW, Sellen A, Heath C, Luff P (1993) One is not enough: multiple views in a media space. In: Proceedings of INTERACT’93 and CHI’93. ACM, New York, pp 335–341
Gibbs JL, Kim H, Boyraz M (2017) Virtual teams. In: The international encyclopedia of organizational communication, pp 1–14. https://www.researchgate.net/profile/Jennifer_Gibbs/publication/314712225_Virtual_Teams/links/5a3d942a0f7e9ba8688e91f6/Virtual-Teams.pdf
Gibson CB, Gibbs JL (2006) Unpacking the concept of virtuality: the effects of geographic dispersion, electronic dependence, dynamic structure, and national diversity on team innovation. Adm Sci Q 51(3):451–495
Gibson CB, McDaniel DM (2010) Moving beyond conventional wisdom: advancements in cross-cultural theories of leadership, conflict, and teams. Perspect Psychol Sci 5(4):450–462
Gibson CB, Gibbs JL, Stanko TL, Tesluk P, Cohen SG (2011) Including the “i” in virtuality and modern job design: extending the job characteristics model to include the moderating effect of individual experiences of electronic dependence and copresence. Organ Sci 22(6):1481–1499
Gibson CB, Huang L, Kirkman BL, Shapiro DL (2014) Where global and virtual meet: the value of examining the intersection of these elements in twenty-first-century teams. Annu Rev Organ Psychol Organ Behav 1(1):217–244
Gilbert D, Tsao J (2000) Exploring Chinese cultural influences and hospitality marketing relationships. Int J Contemp Hosp Manag 12:45–54
Gilson LL, Maynard MT, Jones Young NC, Vartiainen M, Hakonen M (2015) Virtual teams research: 10 years, 10 themes, and 10 opportunities. J Manag 41(5):1313–1337
Glikson E, Wolley AW, Gupta P, Kim YJ (2019) Visualized automatic feedback in virtual teams. Front Psychol 10:814
Google Inc (2017) Google Hangouts. https://hangouts.google.com/
Greenhalgh T, Peacock R (2005) Effectiveness and efficiency of search methods in systematic reviews of complex evidence: audit of primary sources. BMJ 331(7524):1064–1065
Gressgård LJ (2011) Virtual team collaboration and innovation in organizations. Team Perform Manag Int J. https://doi.org/10.1108/dlo.2011.08125daa.007
Article Google Scholar
Grinter RE (2003) Recomposition: coordinating a web of software dependencies. J CSCW 12(3):297–327
Gudykunst WB (1997) Cultural variability in communication: an introduction. Commun Res 24(4):327–348
Hall ET (1976) Beyond culture. Anchor, Garden City
Han SJ, Chae C, Macko P, Park W, Beyerlein M (2017) How virtual team leaders cope with creativity challenges. Eur J Train Dev. https://doi.org/10.1108/EJTD-10-2016-0073
Handley SM, Benton W (2013) The influence of task-and location-specific complexity on the control and coordination costs in global outsourcing relationships. JOM 31(3):109–128
Hardin AM, Fuller MA, Davison RM (2007) I know i can, but can we? Culture and efficacy beliefs in global virtual teams. Small Group Res 38(1):130–155
Harrison DA, Price KH, Gavin JH, Florey AT (2002) Time, teams, and task performance: changing effects of surface-and deep-level diversity on group functioning. Acad Manag J 45(5):1029–1045
Harrison DA, Price KH, Gavin JH, Florey AT (2002) Time, teams, and task performance: changing effects of surface-and deep-level diversity on group functioning. AMJ 45(5):1029–1045
Herbsleb JD, Grinter RE (1999) Splitting the organization and integrating the code: Conway’s law revisited. In: Proceedings of ICSE’99. IEEE, New York, pp 85–95
Herbsleb JD, Mockus A (2003) An empirical study of speed and communication in globally distributed software development. IEEE Trans Softw Eng 29(6):481–494
Herbsleb JD, Mockus A, Finholt TA, Grinter RE (2000) Distance, dependencies, and delay in a global collaboration. In: Proceedings of CSCW’00. ACM, New York, pp 319–328
Hertzum M, Pries-Heje J (2011) Is minimizing interaction a solution to cultural and maturity inequality in offshore outsourcing? In: Balancing sourcing and innovation in information systems development, pp 77–97
Hill NS, Bartol KM (2016) Empowering leadership and effective collaboration in geographically dispersed teams. Pers Psychol 69(1):159–198
Hinds P, Kiesler S (2002) Distributed work. MIT Press, Cambridge
Hinds PJ, Bailey DE (2003) Out of sight, out of sync: understanding conflict in distributed teams. Organ Sci 14(6):615–632
Hinds PJ, Mortensen M (2005) Understanding conflict in geographically distributed teams: the moderating effects of shared identity, shared context, and spontaneous communication. Organ Sci 16(3):290–307
Hoch JE (2013) Shared leadership and innovation: the role of vertical leadership and employee integrity. J Bus Psychol 28(2):159–174
Hoch JE, Dulebohn JH (2017) Team personality composition, emergent leadership and shared leadership in virtual teams: a theoretical framework. Hum Resour Manag Rev 27(4):678–693
Hoch JE, Kozlowski SW (2014) Leading virtual teams: hierarchical leadership, structural supports, and shared team leadership. J Appl Psychol 99(3):390
Hofstede G (1980) Culture’s consequence international differences in work-related values. Sage, Thousand Oaks
Hofstede G (1991) Organizations and cultures: software of the mind. McGraw-Hill, New York
Hofstede G (2001) Culture’s consequences: comparing values, behaviors, institutions and organizations across nations. Sage, Thousand Oaks
Hollenbeck JR, Beersma B, Schouten ME (2012) Beyond team types and taxonomies: a dimensional scaling conceptualization for team description. Acad Manag Rev 37(1):82–106
Holmstrom H, Conchúir EÓ, Agerfalk J, Fitzgerald B (2006) Global software development challenges: a case study on temporal, geographical and socio-cultural distance. In: Proceedings of ICGSE’06. IEEE, New York, pp 3–11
Homan AC, Van Knippenberg D, Van Kleef GA, De Dreu CK (2007) Bridging faultlines by valuing diversity: diversity beliefs, information elaboration, and performance in diverse work groups. J Appl Psychol 92(5):1189
Huang D (2015) Temporal evolution of multi-author papers in basic sciences from 1960 to 2010. Scientometrics 105(3):2137–2147
Hudson SE, Smith I (1996) Techniques for addressing fundamental privacy and disruption trade-offs in awareness support systems. In: Proceedings of CSCW’96. ACM, New York, CSCW’96, pp 248–257. https://doi.org/10.1145/240080.240295
Imsland V, Sahay S, Wartiainen Y (2003) Key issues in managing a global software outsourcing relationship between a Norwegian and Russian firm: some practical implications. In: Proceedings of IRIS26
Inc ZC (2020) Zoom for video, conferencing, and phones. https://zoom.us/
Jakobsen CH, McLaughlin WJ (2004) Communication in ecosystem management: a case study of cross-disciplinary integration in the assessment phase of the Interior Columbia Basin Ecosystem Management Project. Environ Manag 33(5):591–605
Jarvenpaa SL, Leidner DE (1998) Communication and trust in global virtual teams. JCMC 3(4):791–815
Jarvenpaa SL, Shaw TR, Staples DS (2004) Toward contextualized theories of trust: the role of trust in global virtual teams. Inf Syst Res 15(3):250–267
Jehn KA (1997) A qualitative analysis of conflict types and dimensions in organizational groups. Adm Sci Q 42:530–557
Johnson SK, Bettenhausen K, Gibbons E (2009) Realities of working in virtual teams: affective and attitudinal outcomes of using computer-mediated communication. Small Group Res 40(6):623–649
Johnson-Laird PN (1989) Mental models. The MIT Press, London
Kanawattanachai P, Yoo Y (2002) Dynamic nature of trust in virtual teams. J Strateg Inf Syst 11(3–4):187–213
Kaplan AM, Haenlein M (2010) Users of the world, unite! the challenges and opportunities of social media. Bus Horiz 53(1):59–68
Kayworth T, Leidner D (2000) The global virtual manager: a prescription for success. Eur Manag J 18(2):183–194
Kayworth TR, Leidner DE (2002) Leadership effectiveness in global virtual teams. J Manag Inf Syst 18(3):7–40
Kiel L (2003) Experiences in distributed development: a case study. In: Proceedings of international workshop on global software development at ICSE’03
Kiesler S, Cummings JN (2002) What do we know about proximity and distance in work groups? A legacy of research. In: Distributed work, vol 1. MIT Press, Cambridge, pp 57–80
Kimmerle J, Cress U (2007) Group awareness and self-presentation in the information-exchange dilemma: an interactional approach. In: Proceedings of CSCL’07. International Society of the Learning Sciences, New York, pp 370–378
Kirkman BL, Shapiro DL (2005) The impact of cultural value diversity on multicultural team performance. Adv Int Manag 18:33–67
Kirkman BL, Rosen B, Tesluk PE, Gibson CB (2004) The impact of team empowerment on virtual team performance: the moderating role of face-to-face interaction. Acad Manag J 47(2):175–192
Kitchenham B, Brereton P (2013) A systematic review of systematic review process research in software engineering. Inf Softw Technol 55(12):2049–2075. https://doi.org/10.1016/j.infsof.2013.07.010
Kitchenham B, Charters S (2007) Guidelines for performing systematic literature reviews in software engineering version 2.3. Engineering 45(4ve):1051
Kittler MG, Rygl D, Mackinnon A (2011) Special review article: beyond culture or beyond control? Reviewing the use of Hall’s high-/low-context concept. Int J Cross Cult Manag 11(1):63–82
Klitmøller A, Lauring J (2013) When global virtual teams share knowledge: media richness, cultural difference and language commonality. J World Bus 48(3):398–406
Koehne B, Shih PC, Olson JS (2012) Remote and alone: coping with being the remote member on the team. In: Proceedings of CSCW’12. ACM, New York, pp 1257–1266
Kotlarsky J, Oshri I (2005) Social ties, knowledge sharing and successful collaboration in globally distributed system development projects. Eur J Inf Syst 14(1):37–48
Kramer WS, Shuffler ML, Feitosa J (2017) The world is not flat: examining the interactive multidimensionality of culture and virtuality in teams. Hum Resour Manag Rev 27(4):604–620
Kraut RE, Fussell SR, Brennan SE, Siege J (2002) Understanding effects of proximity on collaboration: implications for technologies to support remote collaborative work. In: Hinds P, Kiesler S (eds) Distributed work. MIT Press, Cambridge, pp 137–162
Krishna S, Sahay S, Walsham G (2004) Managing cross-cultural issues in global software outsourcing. Commun ACM 47(4):62–66
Kroll J, Hashmi SI, Richardson I, Audy JL (2013) A systematic literature review of best practices and challenges in follow-the-sun software development. In: Proceedings of international workshop on global software development at ICSE’13. IEEE, New York, pp 18–23
Kuo Fy, Yu Cp (2009) An exploratory study of trust dynamics in work-oriented virtual teams. J Comput Med Commun 14(4):823–854
MathSciNet Google Scholar
Lau DC, Murnighan JK (2005) Interactions within groups and subgroups: the effects of demographic faultlines. Acad Manag J 48(4):645–659
Leung K, Bhagat R, Buchan N, Erez M, Gibson C (2011) Beyond national culture and culture-centricism: an integrating perspective on the role of culture in international business. J Int Bus Stud 42:177–181
Liao C (2017) Leadership in virtual teams: a multilevel perspective. Hum Resour Manag Rev 27(4):648–659
Lipnack J, Stamps J (1997) Virtual teams: reaching across space, time, and organizations with technology. Wiley, New York
Livingston G, Waring B, Pacheco LF, Buchori D, Jiang Y, Gilbert L, Jha S (2016) Perspectives on the global disparity in ecological science. Bioscience 66(2):147–155
López G, Guerrero LA (2014) Notifications for collaborative documents editing. In: Proceedings of UCAmI’14. Springer, Berlin, pp 80–87
López G, Guerrero LA (2017) Awareness supporting technologies used in collaborative systems: a systematic literature review. In: Proceedings of CSCW’17. ACM, New York, pp 808–820
Lowry PB, Zhang D, Zhou L, Fu X (2010) Effects of culture, social presence, and group composition on trust in technology-supported decision-making groups. Inf Syst J 20(3):297–315
Lu LC, Chang HH, Yu ST (2011) The role of individualism and collectivism in consumer perceptions toward e-retailers’ ethics. In: 2011 international conference on information management, innovation management and industrial engineering, vol 2. IEEE, New York, pp 194–197
Malhotra A, Majchrzak A, Rosen B (2007) Leading virtual teams. Acad Manag Perspect 21(1):60–70
Malone TW, Crowston K (1994) The interdisciplinary study of coordination. CSUR 26(1):87–119
Mannix EA, Griffith T, Neale MA (2002) The phenomenology of conflict in distributed work teams. In: Hinds P, Kiesler S (eds) Distributed work. The MIT Press, Cambridge, pp 213–233
Mantei MM, Baecker RM, Sellen AJ, Buxton WA, Milligan T, Wellman B (1991) Experiences in the use of a media space. In: Proceedings of CHI’91. ACM, New York, pp 203–208
Mark G (2002) Extreme collaboration. Commun ACM 45(6):89–93
Marlow J, Dabbish L (2012) Designing interventions to reduce psychological distance in globally distributed teams. In: Proceedings of CSCW’12 companion. ACM, New York, pp 163–166
Marlow SL, Lacerenza CN, Salas E (2017) Communication in virtual teams: a conceptual framework and research agenda. Hum Resour Manag Rev 27(4):575–589
Martins LL, Shalley CE (2011) Creativity in virtual work: effects of demographic differences. Small Group Res 42(5):536–561
Maruping LM, Agarwal R (2004) Managing team interpersonal processes through technology: a task-technology fit perspective. J Appl Psychol 89(6):975
Maruping LM, Magni M (2015) Motivating employees to explore collaboration technology in team contexts. Mis Quarterly 39(1):1–16
Mattessich PW, Monsey BR (1992) Collaboration: what makes it work. A review of research literature on factors influencing successful collaboration. ERIC, St. Paul
Maynard MT, Gilson LL (2014) The role of shared mental model development in understanding virtual team effectiveness. Group Organ Manag 39(1):3–32
Maynard MT, Mathieu JE, Rapp TL, Gilson LL (2012) Something (s) old and something (s) new: modeling drivers of global virtual team effectiveness. J Organ Behav 33(3):342–365
McDonough EF, Kahnb KB, Barczaka G (2001) An investigation of the use of global, virtual, and colocated new product development teams. J Prod Innov Manag 18(2):110–120
McGuffin LJ, Olson GM (1992) ShrEdit: a shared electronic work space. University of Michigan, Cognitive Science and Machine Intelligence Laboratory, Ann Arbor
McIntyre NE, Knowles-Yánez K, Hope D (2000) Urban ecology as an interdisciplinary field: differences in the use of “‘urban” between the social and natural sciences. Urban Ecosys 4(1):5–24
McNamara K, Dennis AR, Carte TA (2008) It’s the thought that counts: the mediating effects of information processing in virtual team decision making. Inf Syst Manag 25(1):20–32
Meyerson D, Weick KE, Kramer RM et al (1996) Swift trust and temporary groups. Trust Organ Front Theory Res 166:195
Microsoft (2017) Skype. http://www.skype.com/en/
Microsoft (2020) Microsoft teams. https://products.office.com/en-us/microsoft-teams/group-chat-software
Milliken FJ, Martins LL (1996) Searching for common threads: understanding the multiple effects of diversity in organizational groups. Acad Manag Rev 21(2):402–433
Montoya MM, Massey AP, Hung YTC, Crisp CB (2009) Can you hear me now? Communication in virtual product development teams. J Prod Innov Manag 26(2):139–155
Mortensen M, Hinds PJ (2001) Conflict and shared identity in geographically distributed teams. Int J Confl Manag 12(3):212–238
Navimipour NJ, Charband Y (2016) Knowledge sharing mechanisms and techniques in project teams: literature review, classification, and current trends. Comput Hum Behav 62:730–742
Neuliep JW (2020) Intercultural communication: a contextual approach. Sage, Thousand Oaks
Newman SA, Ford RC, Marshall GW (2019) Virtual team leader communication: employee perception and organizational reality. Int J Bus Commun. https://doi.org/10.1177/2329488419829895
Nguyen-Duc A, Cruzes D, Conradi R (2012) Dispersion, coordination and performance in global software teams: a systematic review. In: Proceedings of ESEM’12. ACM, New York, pp 129–138
Nguyen-Duc A, Cruzes DS, Conradi R (2015) The impact of global dispersion on coordination, team performance and software quality—a systematic literature review. Inf Softw Technol 57:277–294
Noll J, Beecham S, Richardson I (2010) Global software development and collaboration: barriers and solutions. ACM Inroads 1(3):66–78
O’Hara-Devereaux M, Johansen R (1994) Globalwork: bridging distance, culture, and time. Jossey-Bass Pub, San Francisco
O’Leary MB, Cummings JN (2007) The spatial, temporal, and configurational characteristics of geographic dispersion in teams. Manag Inf Syst Q 31(3):433–452
O’Leary MB, Mortensen M (2010) Go (con) figure: subgroups, imbalance, and isolates in geographically dispersed teams. Organ Sci 21(1):115–131
O’Leary MB, Wilson JM, Metiu A (2012) Beyond being there: the symbolic role of communication and identification in the emergence of perceived proximity in geographically dispersed work. ESSEC working paper 1112
Olson G, Ackerman M, Atkins D, Bos N, Derrick C, Cohen M, Finholt T, Furnas G, Hedstrom M, Herbsleb J, Myers J, Olson J, Prakash A, Radev D, Teasley S, Trimble J, Weymouth T, Elizabeth Yakel, Zimmerman A, Cooney D, Hardin J, Hofer E, Knoop P, Peters G, Verhey-Henke A, Bietz M, Birnholtz J, Luo A, Potter A, Puetz M, Yew J (2006) Science of collaboratories. http://soc.ics.uci.edu/
Olson GM, Olson JS (2000) Distance matters. Hum Comput Interact 15(2):139–178
Olson GM, Zimmerman A, Bos N (2008) Scientific collaboration on the Internet. The MIT Press, Cambridge
Olson JS, Olson GM (2006) Bridging distance: empirical studies of distributed teams. In: Proceedings of human factors in MIS’06, vol 2, pp 27–30
Olson JS, Olson GM (2013) Working together apart: collaboration over the internet. Synth Lect Hum Center Inform 6(5):1–151
O’Reilly CA, Williams KY, Barsade S (1997) Demography and group performance: does diversity help? Graduate School of Business, Stanford University, Stanford
Orlikowski WJ (2002) Knowing in practice: enacting a collective capability in distributed organizing. Organ Sci 13(3):249–273
Otjacques B, McCall R, Feltz F (2006) An ambient workplace for raising awareness of internet-based cooperation. In: Proceedings of CDVE’06. LNCS, London, pp 275–286
O’Neill TA, Hancock SE, Zivkov K, Larson NL, Law SJ (2016) Team decision making in virtual and face-to-face environments. Group Decis Negot 25(5):995–1020
Pan RK, Kaski K, Fortunato S (2012) World citation and collaboration networks: uncovering the role of geography in science. Sci Rep 2:902
Parreira MR, Machado KB, Logares R, Diniz-Filho JAF, Nabout JC (2017) The roles of geographic distance and socioeconomic factors on international collaboration among ecologists. Scientometrics 113(3):1539–1550
Patel H, Pettitt M, Wilson JR (2012) Factors of collaborative working: a framework for a collaboration model. Appl Ergon 43(1):1–26
Paul DL, McDaniel RR Jr (2004) A field study of the effect of interpersonal trust on virtual collaborative relationship performance. Manag Inf Syst Q 28:183–227
Pearce WB (1974) Trust in interpersonal communication. CM 41(3):236–44
Pelled LH (1996) Demographic diversity, conflict, and work group outcomes: an intervening process theory. Organ Sci 7(6):615–631
Pelled LH, Eisenhardt KM, Xin KR (1999) Exploring the black box: an analysis of work group diversity, conflict and performance. Adm Sci Q 44(1):1–28
Pe narroja V, Orengo V, Zornoza A, Hernández A (2013) The effects of virtuality level on task-related collaborative behaviors: the mediating role of team trust. Comput Hum Behav 29(3):967–974
Pe narroja V, Orengo V, Zornoza A (2017) Reducing perceived social loafing in virtual teams: the effect of team feedback with guided reflexivity. J Appl Soc Psychol 47(8):424–435
Pinjani P, Palvia P (2013) Trust and knowledge sharing in diverse global virtual teams. Inf Manag 50(4):144–153
Pivotal Software (2017) Agile project management. https://www.pivotaltracker.com/
Polzer JT, Crisp CB, Jarvenpaa SL, Kim JW (2006) Extending the faultline model to geographically dispersed teams: how colocated subgroups can impair group functioning. Acad Manag J 49(4):679–692
Ponds R, Van Oort F, Frenken K (2007) The geographical and institutional proximity of research collaboration. Pap Reg Sci 86(3):423–443
Rains SA (2005) Leveling the organizational playing field-virtually: a meta-analysis of experimental research assessing the impact of group support system use on member influence behaviors. Commun Res 32(2):193–234
Ramasubbu N, Cataldo M, Balan RK, Herbsleb JD (2011) Configuring global software teams: a multi-company analysis of project productivity, quality, and profits. In: Proceedings of ICSE’11. ACM, New York, pp 261–270
Raymond E (1999) Homesteading the Noosphere, the Cathedral, and the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary. O’Reilly & Associates, Sebastopol Calf
Robert LP (2016) Far but near or near but far? The effects of perceived distance on the relationship between geographic dispersion and perceived diversity. In: Proceedings of CHI’16. ACM, New York, pp 2461–2473. https://doi.org/10.1145/2858036.2858534
Robert LP, Denis AR, Hung YTC (2009) Individual swift trust and knowledge-based trust in face-to-face and virtual team members. J Manag Inf Syst 26(2):241–279
Robert LP Jr, You S (2018) Are you satisfied yet? Shared leadership, individual trust, autonomy, and satisfaction in virtual teams. J Assoc Inf Sci Technol 69(4):503–513
Rusman E, Van Bruggen J, Sloep P, Koper R (2010) Fostering trust in virtual project teams: towards a design framework grounded in a trustworthiness antecedents (TWAN) schema. Int J Hum Comput Stud 68(11):834–850
Sarker S, Sahay S (2004) Implications of space and time for distributed work: an interpretive study of US–Norwegian systems development teams. Eur J Inf Syst 13(1):3–20
Sarker S, Ahuja M, Sarker S, Kirkeby S (2011) The role of communication and trust in global virtual teams: a social network perspective. J Manag Inf Syst 28(1):273–310
Saunders C, Van Slyke C, Vogel DR (2004) My time or yours? Managing time visions in global virtual teams. Acad Manag Perspect 18(1):19–37
Saunders C, Van Slyke C, Vogel DR (2004) My time or yours? Managing time visions in global virtual teams. Acad Manag J 18(1):19–37
Schaubroeck JM, Yu A (2017) When does virtuality help or hinder teams? Core team characteristics as contingency factors. Hum Resour Manag Rev 27(4):635–647
Schmidt K (2002) The problem with “awareness”: introductory remarks on “awareness in CSCW”. Comput Supported Coop Work 11(3):285–298. https://doi.org/10.1023/A:1021272909573
Schmidt K, Bannon L (1992) Taking CSCW seriously. J CSCW 1(1–2):7–40
Schmidtke JM, Cummings A (2017) The effects of virtualness on teamwork behavioral components: the role of shared mental models. Hum Resour Manag Rev 27(4):660–677
Schneier CE, Goktepe JR (1983) Issues in emergent leadership: the contingency model of leadership, leader sex, leader behavior. Small Groups Soc Interact 1:413–421
Scott CPR, Wildman JL (2015) Culture, communication, and conflict: a review of the global virtual team literature. Springer, New York, pp 13–32
Scrumwise Inc (2017) The easiest scrum tool you’ll find. https://www.scrumwise.com/
See M (2018) 18 international collaboration: are the challenges worth the benefits? J Anim Sci 96(suppl–3):2–2
Siebdrat F, Hoegl M, Ernst H (2014) Subjective distance and team collaboration in distributed teams. J Prod Innov Manag 31(4):765–779
Slack (2017) Where work happens. https://slack.com/
Šmite D, Wohlin C, Gorschek T, Feldt R (2010) Empirical evidence in global software engineering: a systematic review. Empir Softw Eng 15(1):91–118
Sole D, Edmondson A (2002) Situated knowledge and learning in dispersed teams. Br J Manag 13(S2):S17–S34
Solomon C (2016) Trends in global virtual teams. https://www.rw-3.com/resource-center/2016-survey-report-trends-in-global-virtual-teams
Srivastava A, Bartol KM, Locke EA (2006) Empowering leadership in management teams: effects on knowledge sharing, efficacy, and performance. Acad Manag J 49(6):1239–1251
Stahl GK, Maznevski ML, Voigt A, Jonsen K (2010) Unraveling the effects of cultural diversity in teams: a meta-analysis of research on multicultural work groups. J Int Bus Stud 41(4):690–709
Staples DS, Zhao L (2006) The effects of cultural diversity in virtual teams versus face-to-face teams. Group Decis Negot 15(4):389–406
Steinmacher I, Chaves AP, Gerosa MA (2013) Awareness support in distributed software development: a systematic review and mapping of the literature. J CSCW 22(2–3):113–158
Straub D, Loch K, Evaristo R, Karahanna E, Srite M (2002) Toward a theory-based measurement of culture. J Glob Inf Manag (JGIM) 10(1):13–23
Strauss A (1988) The articulation of project work: an organizational process. Sociol Q 29:163–178
Swigger K, Alpaslan F, Brazile R, Monticino M (2004) Effects of culture on computer-supported international collaborations. Int J Hum Comput Stud 60(3):365–380
Tang JC, Zhao C, Cao X, Inkpen K (2011) Your time zone or mine? A study of globally time zone-shifted collaboration. In: Proceedings of CSCW’11. ACM, New York, pp 235–244
Tangirala S, Alge BJ (2006) Reactions to unfair events in computer-mediated groups: a test of uncertainty management theory. Organ Behav Hum Decis Process 100(1):1–20
Taras V, Kirkman BL, Steel P (2010) Examining the impact of culture’s consequences: a three-decade, multilevel, meta-analytic review of Hofstede’s cultural value dimensions. J Appl Psychol 95(3):405
Teasley S, Covi L, Krishnan MS, Olson JS (2000) How does radical collocation help a team succeed? In: Proceedings of CSCW’00. ACM, New York, pp 339–346
Tenopir C, Allard S, Douglass K, Aydinoglu AU, Wu L, Read E, Manoff M, Frame M (2011) Data sharing by scientists: practices and perceptions. PLoS ONE 6(6):e21101
Tenzer H, Pudelko M, Harzing AW (2014) The impact of language barriers on trust formation in multinational teams. J Int Bus Stud 45(5):508–535
Tran H, Zdun U et al (2017) Systematic review of software behavioral model consistency checking. CSUR 50(2):17
Treinen JJ, Miller-Frost SL (2006) Following the sun: case studies in global software development. IBM J Res Dev 45(4):773–783
Trello Inc (2017) Trello. https://trello.com/
Tress G, Tress B, Fry G (2007) Analysis of the barriers to integration in landscape research projects. Land Use Policy 24(2):374–385
Triandis HC, Singelis TM (1998) Training to recognize individual differences in collectivism and individualism within culture. Int J Intercult Relat 22(1):35–47
Triandis HC, Bontempo R, Villareal MJ, Asai M, Lucca N (1988) Individualism and collectivism: cross-cultural perspectives on self-ingroup relationships. J Pers Soc Psychol 54(2):323
Umphress EE, Smith-Crowe K, Brief AP, Dietz J, Watkins MB (2007) When birds of a feather flock together and when they do not: status composition, social dominance orientation, and organizational attractiveness. J Appl Psychol 92(2):396
Vaccaro A, Veloso F, Brusoni S (2009) The impact of virtual technologies on knowledge-based processes: an empirical study. Res Policy 38(8):1278–1287
Van den Bulte C, Moenaert RK (1998) The effects of R&D team co-location on communication patterns among R&D, marketing, and manufacturing. Manag Sci 44(11–part–2):S1–S18
MATH Google Scholar
van Solingen R, Basili V, Caldiera G, Rombach HD (2002) Goal question metric (GQM) approach. In: Marciniak JJ (ed) Encyclopedia of software engineering. https://doi.org/10.1002/0471028959.sof142
Van Weijen D (2012) The language of (future) scientific communication. Res Trends 31(11):2012
Wakefield RL, Leidner DE, Garrison G (2008) Research note—a model of conflict, leadership, and performance in virtual teams. Inf Syst Res 19(4):434–455
Walsh JP, Maloney NG (2007) Collaboration structure, communication media, and problems in scientific work teams. J Comput Mediat Commun 12(2):712–732
Walther JB, Bunz U (2005) The rules of virtual groups: trust, liking, and performance in computer-mediated communication. J Commun 55(4):828–846
Warkentin ME, Sayeed L, Hightower R (1997) Virtual teams versus face-to-face teams: an exploratory study of a web-based conference system. Decis Sci 28(4):975–996
Watson WE, Kumar K, Michaelsen LK (1993) Cultural diversity’s impact on interaction process and performance: comparing homogeneous and diverse task groups. Acad Manag J 36(3):590–602
Watson-Manheim MB, Chudoba KM, Crowston K (2002) Discontinuities and continuities: a new way to understand virtual work. ITP 15(3):191–209
Watson-Manheim MB, Chudoba KM, Crowston K (2012) Perceived discontinuities and constructed continuities in virtual work. Inf Syst J 22(1):29–52
Weinel M, Bannert M, Zumbach J, Hoppe HU, Malzahn N (2011) A closer look on social presence as a causing factor in computer-mediated collaboration. Comput Hum Behav 27(1):513–521
Wiersema MF, Bantel KA (1992) Top management team demography and corporate strategic change. Acad Manag J 35(1):91–121
Williams K, O’Reilly C III (1998) Demography and diversity in organisations: a review of 40 years of research. In: Staw BM, Cummings LL (eds) Research in organisational behaviour. Jai Pres, Greenwich
Wilson JM, Boyer O’Leary M, Metiu A, Jett QR (2008) Perceived proximity in virtual work: explaining the paradox of far-but-close. Organ Stud 29(7):979–1002
Zander L, Zettinig P, Mäkelä K (2013) Leading global virtual teams to success. Org Dyn 42(3 SI):228–237
Zellmer-Bruhn ME, Gibson CB (2013) How does culture matter. In: Yuki M, Brewer M (eds) Culture and group processes, p 166. https://books.google.com/books?hl=en&lr=&id=DtI8BAAAQBAJ&oi=fnd&pg=PA166&dq=Zellmer-Bruhn+ME,+Gibson+CB+(2013)+How+does+culture+matter.+In:+Culture+and+group+processes,+p+166&ots=wE-qqLV173&sig=svs8MQKVi40vMB_fixB86FyRmdQ#v=onepage&q&f=false
Zolin R, Hinds PJ, Fruchter R, Levitt RE (2004) Interpersonal trust in cross-functional, geographically distributed work: a longitudinal study. Inf Organ 14(1):1–26
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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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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.
Abarca, V. M. G., Palos-Sanchez, P. R., and Rus-Arias, E. (2020). Working in virtual teams: a systematic literature review and a bibliometric analysis. IEEE Access 8, 168923–168940. doi: 10.1109/access.2020.3023546
CrossRef Full Text | Google Scholar
Alsharo, M., Gregg, D., and Ramirez, R. (2017). Virtual team effectiveness: the role of knowledge sharing and trust. Inf. Manage. 54, 479–490. doi: 10.1016/j.im.2016.10.005
Altschuller, S., and Benbunan-Fich, R. (2010). Trust, performance, and the communication process in ad hoc decision-making virtual teams. J. Comput.Mediat. Commun. 16, 27–47. doi: 10.1111/j.1083-6101.2010.01529.x
Andressen, P., Konradt, U., and Neck, C. P. (2012). The relation between self-leadership and transformational leadership: competing models and the moderating role of virtuality. J. Leadersh. Organ. Stud. 19, 68–82. doi: 10.1177/1548051811425047
Baard, S. K., Rench, T. A., and Kozlowski, S. W. J. (2014). Performance adaptation: a theoretical integration and review. J. Manage. 40, 48–99. doi: 10.1177/0149206313488210
Bagozzi, R. P., and Yi, Y. (1988). On the evaluation of structural equation models. J. Acad. Mark. Sci. 16, 74–94.
Google Scholar
Baltes, B. B., Dickson, M. W., Sherman, M. P., Bauer, C. C., and LaGanke, J. S. (2002). Computer-mediated communication and group decision making: a meta-analysis. Organ. Behav. Hum. Decis. Process. 87, 156–179. doi: 10.1006/obhd.2001.2961
Balthazard, P. A., Waldman, D. A., and Warren, J. E. (2009). Predictors of the emergence of transformational leadership in virtual decision teams. Leadersh. Q. 20, 651–663. doi: 10.1016/j.leaqua.2009.06.008
Barclay, D., Higgins, C., and Thompson, R. (1995). The partial least squares (PLS) approach to casual modeling: personal computer adoption ans use as an Illustration. Technol. Stud. 2, 285–309.
Bell, M., Robertson, D., Weeks, M., and Yu, D. (2002). A virtual team group process. Can. J. Nur. Leadersh. 15, 30–33. doi: 10.12927/cjnl.2002.19157
PubMed Abstract | CrossRef Full Text | Google Scholar
Bormann, E. G. (1983). “Symbolic convergence: organizational communication and culture,” in Communication and Organizations: An Interpretive Approach , eds L. Putnam and M. E. Pacanowsky, (Thousand Oaks, CA: SAGE Publications), 99–122.
Bormann, E. G. (1996). Symbolic convergence theory and communication in group decision making. Commun. Group Decis. Making 2, 81–113. doi: 10.4135/9781452243764.n4
Bormann, E. G., Craan, J. F., and Shields, D. C. (1994). In defense of symbolic convergence theory: a look at the theory and its criticisms after two decades. Commun. Theory 4, 259–294. doi: 10.1111/j.1468-2885.1994.tb00093.x
Bormann, E. G., Knutson, R. L., and Musolf, K. (1997). Why do people share fantasies? An empirical investigation of a basic tenet of the symbolic convergence communication theory. Commun. Stud. 48, 254–276. doi: 10.1080/10510979709368504
Boudreau, M.-C., Gefen, D., and Straub, D. W. (2001). Validation in information systems research: a state-of-the-art assessment. MIS Q. 25, 1–16. doi: 10.2307/3250956
Brahm, T., and Kunze, F. (2012). The role of trust climate in virtual teams. J. Manage. Psychol. 27, 595–614. doi: 10.1108/02683941211252446
Brett, J., Behfar, K., and Kern, M. C. (2006). Managing Multicultural Teams. Brighton, MA: Harvard Business Review.
Brooks, S. K., Webster, R. K., Smith, L. E., Woodland, L., Wessely, S., Greenberg, N., et al. (2020). The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet 395, 912–920. doi: 10.1016/s0140-6736(20)30460-8
Bryant, S. M., Albring, S. M., and Murthy, U. (2009). The effects of reward structure, media richness and gender on virtual teams. Int. J. Account. Inf. Syst. 10, 190–213. doi: 10.1016/j.accinf.2009.09.002
Burke, C. S., Stagl, K. C., Klein, C., Goodwin, G. F., Salas, E., and Halpin, S. M. (2006). What type of leadership behaviors are functional in teams? A meta-analysis. Leadersh. Q. 17, 288–307. doi: 10.1016/j.leaqua.2006.02.007
Campion, M. A., Medsker, G. J., and Higgs, A. C. (1993). Relations between work group characteristics and effectiveness: implications for designing effective work groups. Pers. Psychol. 46, 823–847. doi: 10.1111/j.1744-6570.1993.tb01571.x
Chen, C., de Rubens, G. Z., Xu, X., and Li, J. (2020). Coronavirus comes home? Energy use, home energy management, and the social-psychological factors of COVID-19. Energy Res. Soc. Sci. 68, 101688. doi: 10.1016/j.erss.2020.101688
Chin, W. W. (1998). The partial least squares aproach to structural equation modeling. Mod. Methods Bus. Res. 295, 295–336.
Chin, W. W. (2010). “How to write up and report PLS analyses,” in Handbook of Partial Least Squares , eds H. Wang, J. Henseler, V. E. Vinzi, and W. W. Chin, (Berlin: Springer), 655–690. doi: 10.1007/978-3-540-32827-8_29
Chin, W. W., and Newsted, P. R. (1999). Structural equation modeling analysis with small samples using partial least squares. Stat. Strategies Small Sample Res. 1, 307–341.
Coppola, N. W., Hiltz, S. R., and Rotter, N. G. (2004). Building trust in virtual teams. IEEE Trans. Prof. Commun. 47, 95–104. doi: 10.1109/TPC.2004.828203
Cramton, C. D., and Webber, S. S. (2005). Relationships among geographic dispersion, team processes, and effectiveness in software development work teams. J. Bus. Res. 58, 758–765. doi: 10.1016/j.jbusres.2003.10.006
Crisp, C. B., and Jarvenpaa, S. L. (2013). Swift trust in global virtual teams. J. Pers. Psychol. 12, 45–56. doi: 10.1027/1866-5888/a000075
Cummings, J. N., and Haas, M. R. (2012). So many teams, so little time: time allocation matters in geographically dispersed teams. J. Organ. Behav. 33, 316–341. doi: 10.1002/job.777
Daft, R. L., and Lengel, R. H. (1986). Organizational information requirements, media richness and structural design. Manage. Sci. 32, 554–571. doi: 10.1287/mnsc.32.5.554
Daft, R. L., and Macintosh, N. B. (1981). A tentative exploration into the amount and equivocality of information processing in organizational work units. Adm. Sci. Q. 26, 207–224. doi: 10.2307/2392469
David Strang, K. (2011). Leadership substitutes and personality impact on time and quality in virtual new product development projects. Proj. Manage. J. 42, 73–90. doi: 10.1002/pmj.20208
Dayan, M., and Di Benedetto, C. A. (2010). The impact of structural and contextual factors on trust formation in product development teams. Ind. Mark. Manage. 39, 691–703. doi: 10.1016/j.indmarman.2010.01.001
De Jong, B. A., and Elfring, T. (2010). How does trust affect the performance of ongoing teams? The mediating role of reflexivity, monitoring, and effort. Acad. Manage. J. 53, 535–549. doi: 10.5465/amj.2010.51468649
de Ven, A. H., Delbecq, A. L., and Koenig, R. Jr. (1976). Determinants of coordination modes within organizations. Am. Soc. Rev. 41, 322–338. doi: 10.2307/2094477
Dennis, A. R., and Kinney, S. T. (1998). Testing media richness theory in the new media: the effects of cues, feedback, and task equivocality. Inf. Syst. Res. 9, 256–274. doi: 10.1287/isre.9.3.256
Duarte, D. L., and Snyder, N. T. (2006). Mastering Virtual Teams: Strategies, Tools, and Techniques that Succeed. Hoboken, NJ: John Wiley & Sons.
Dulebohn, J. H., and Hoch, J. E. (2017). Virtual teams in organizations. Hum. Resour. Manage. Rev. 27, 569–574. doi: 10.1016/j.hrmr.2016.12.004
Duncan, R. B. (1972). Characteristics of organizational environments and perceived environmental uncertainty. Adm. Sci. Q. 17, 313–327. doi: 10.2307/2392145
Ebrahim, N. A., Ahmed, S., and Taha, Z. (2009). Virtual teams: a literature review. Aust. J. Basic Appl. Sci. 3, 2653–2669.
Evans, C. R., and Dion, K. L. (1991). Group cohesion and performance: a meta-analysis. Small Group Res. 22, 175–186. doi: 10.1177/1046496491222002
Fornell, C., and Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18, 39–50. doi: 10.2307/3151312
Fuller, M. A., Hardin, A. M., and Davison, R. M. (2006). Efficacy in technology-mediated distributed teams. J. Manage. Inf. Syst. 23, 209–235. doi: 10.2753/mis0742-1222230308
Furumo, K. (2009). The impact of conflict and conflict management style on deadbeats and deserters in virtual teams. J. Comput. Inf. Syst. 49, 66–73.
Galbraith, J. R. (1973). Designing Complex Organizations. Boston, MA: Addison-Wesley Longman Publishing Co., Inc.
Garrison, G., Wakefield, R. L., Xu, X., and Kim, S. H. (2010). Globally distributed teams: the effect of diversity on trust, cohesion and individual performance. ACM SIGMIS Database Database Adv. Inf. Syst. 41, 27–48. doi: 10.1145/1851175.1851178
Geber, B. (1995). Virtual teams. Training 32, 36–40.
Gilson, L. L., Maynard, M. T., Young, N. C. J., Vartiainen, M., and Hakonen, M. (2015). Virtual teams research: 10 Years, 10 themes, and 10 opportunities. J. Manage. 41, 1313–1337. doi: 10.1177/0149206314559946
Glückler, J., and Schrott, G. (2007). Leadership and performance in virtual teams: exploring brokerage in electronic communication. Int. J. E-Collaboration (IJeC) 3, 31–52. doi: 10.4018/jec.2007070103
Goh, S., and Wasko, M. (2012). The effects of leader-member exchange on member performance in virtual world teams. J. Assoc. Inf. Syst. 13, 861–885. doi: 10.17705/1jais.00308
Gondal, A. M., and Khan, A. (2008). Impact of team empowerment on team performance: case of the telecommunications industry in Islamabad. Int. Rev. Bus. Res. Papers 4, 138–146.
Griffin, E. (1997). Groupthink. A First Look at Communication Theory. New York, NY: McGraw-Hill Education.
Guzzo, R. A., Yost, P. R., Campbell, R. J., and Shea, G. P. (1993). Potency in groups: articulating a construct. Br. J. Soc. Psychol. 32, 87–106. doi: 10.1111/j.2044-8309.1993.tb00987.x
Hair, J. F., Ringle, C. M., and Sarstedt, M. (2011). PLS-SEM: indeed a silver bullet. J. Mark. Theory Pract. 19, 139–152. doi: 10.2753/mtp1069-6679190202
Hair, J. F., Ringle, C. M., and Sarstedt, M. (2013). Partial least squares structural equation modeling: rigorous applications, better results and higher acceptance. Long Range Plan. 46, 1–12. doi: 10.1016/j.lrp.2013.01.001
Han, H.-J., Hiltz, S. R., Fjermestad, J., and Wang, Y. (2011). Does medium matter? A comparison of initial meeting modes for virtual teams. IEEE Trans. Prof. Commun. 54, 376–391. doi: 10.1109/tpc.2011.2175759
Henderson, L. S. (2008). The impact of project managers’ communication competencies: validation and extension of a research model for virtuality, satisfaction, and productivity on project teams. Proj. Manage. J. 39, 48–59. doi: 10.1002/pmj.20044
Henseler, J. (2017). Bridging design and behavioral research with variance-based structural equation modeling. J. Adv. 46, 178–192. doi: 10.1080/00913367.2017.1281780
Henseler, J., Hubona, G., and Ray, P. A. (2016). Using PLS path modeling in new technology research: updated guidelines. Ind. Manage. Data Syst. 116, 2–20. doi: 10.1108/imds-09-2015-0382
Henttonen, K., and Blomqvist, K. (2005). Managing distance in a global virtual team: the evolution of trust through technology-mediated relational communication. Strategic Change 14, 107–119. doi: 10.1002/jsc.714
Hertel, G., Geister, S., and Konradt, U. (2005). Managing virtual teams: a review of current empirical research. Hum. Resour. Manage. Rev. 15, 69–95. doi: 10.1016/j.hrmr.2005.01.002
Hoch, J. E., and Kozlowski, S. W. J. (2014). Leading virtual teams: hierarchical leadership, structural supports, and shared team leadership. J. Appl. Psychol. 99, 390–403. doi: 10.1037/a0030264
Hogg, M. A. (1987). “Social identity and group cohesiveness,” in Rediscovering the Social Group: A Self-Categorization Theory , ed. J. Turner, (New York, NY: Basil Blackwell), 89–116.
Hogg, M. A., and Tindale, R. S. (2001). Group Processes. Malden, MA: Blackwell.
Hu, L., and Bentler, P. M. (1998). Fit indices in covariance structure modeling: sensitivity to underparameterized model misspecification. Psychol. Methods 3:424. doi: 10.1037/1082-989x.3.4.424
Huang, R., Kahai, S., and Jestice, R. (2010). The contingent effects of leadership on team collaboration in virtual teams. Comput. Hum. Behav. 26, 1098–1110. doi: 10.1016/j.chb.2010.03.014
Jarrahi, M. H., and Sawyer, S. (2013). Social technologies, informal knowledge practices, and the enterprise. J. Organ. Comput. Electron. Commer. 23, 110–137. doi: 10.1080/10919392.2013.748613
Joshi, A., Lazarova, M. B., and Liao, H. (2009). Getting everyone on board: the role of inspirational leadership in geographically dispersed teams. Organ. Sci. 20, 240–252. doi: 10.1287/orsc.1080.0383
Kerr, S., and Jermier, J. M. (1978). Substitutes for leadership: their meaning and measurement. Organ. Behav. Hum. Perf. 22, 375–403. doi: 10.1016/0030-5073(78)90023-5
Kirkman, B. L., Cordery, J. L., Mathieu, J., Rosen, B., and Kukenberger, M. (2013). Global organizational communities of practice: the effects of nationality diversity, psychological safety, and media richness on community performance. Hum. Relations 66, 333–362. doi: 10.1177/0018726712464076
Kirkman, B. L., Rosen, B., Tesluk, P. E., and Gibson, C. B. (2004). The impact of team empowerment on virtual team performance: the moderating role of face-to-face interaction. Acad. Manage. J. 47, 175–192. doi: 10.5465/20159571
Kock, N., and Lynn, G. S. (2012). Electronic media variety and virtual team performance: the mediating role of task complexity coping mechanisms. IEEE Trans. Prof. Commun. 55, 325–344. doi: 10.1109/TPC.2012.2208393
Konradt, U., and Hoch, J. E. (2007). A work roles and leadership functions of managers in virtual teams. Int. J. E-Collaboration (IJeC) 3, 16–35. doi: 10.4018/jec.2007040102
Kort, E. D. (2008). What, after all, is leadership?‘Leadership’and plural action. Leadersh. Q. 19, 409–425. doi: 10.1016/j.leaqua.2008.05.003
Lin, C., Standing, C., and Liu, Y.-C. (2008). A model to develop effective virtual teams. Decis. Support Syst. 45, 1031–1045. doi: 10.1016/j.dss.2008.04.002
Lott, A. J., and Lott, B. E. (1965). Group cohesiveness as interpersonal attraction: a review of relationships with antecedent and consequent variables. Psychol. Bull. 64:259. doi: 10.1037/h0022386
Lowry, P. B., Roberts, T. L., Romano, N. C. Jr., Cheney, P. D., and Hightower, R. T. (2006). The impact of group size and social presence on small-group communication: does computer-mediated communication make a difference? Small Group Res. 37, 631–661. doi: 10.1177/1046496406294322
Lowry, P. B., Zhang, D., Zhou, L., and Fu, X. (2010). Effects of culture, social presence, and group composition on trust in technology-supported decision-making groups. Inf. Syst. J. 20, 297–315. doi: 10.1111/j.1365-2575.2009.00334.x
Lu, L. (2015). Building trust and cohesion in virtual teams: the developmental approach. J. Organ. Eff. People Perf. 2, 55–72. doi: 10.1108/JOEPP-11-2014-0068
Makoul, G., and Curry, R. H. (2007). The value of assessing and addressing communication skills. Jama 298, 1057–1059. doi: 10.1001/jama.298.9.1057
Martinez-Cañas, R., Ruiz-Palomino, P., Linuesa-Langreo, J., and Blázquez-Resino, J. J. (2016). Consumer participation in co-creation: an enlightening model of causes and effects based on ethical values and transcendent motives. Front. Psychol. 7:793. doi: 10.3389/fpsyg.2016.00793
Martins, L. L., Gilson, L. L., and Maynard, M. T. (2004). Virtual teams: what do we know and where do we go from here? J. Manage. 30, 805–835. doi: 10.1016/j.jm.2004.05.002
Maynard, M. T., Mathieu, J. E., Rapp, T. L., and Gilson, L. L. (2012). Something(s) old and something(s) new: modeling drivers of global virtual team effectiveness. J. Organ. Behav. 33, 342–365. doi: 10.1002/job.1772
McBer and Company. (1980). Trainer’s Guide. Boston, MA: McBer and Company.
Mohr, L. B. (1971). Organizational technology and organizational structure. Adm. Sci. Q. 16, 444–459. doi: 10.2307/2391764
Montoya-Weiss, M. M., Massey, A. P., and Song, M. (2001). Getting it together: temporal coordination and conflict management in global virtual teams. Acad. Manage. J. 44, 1251–1262. doi: 10.2307/3069399
Palos, P. R., and Correia, M. B. (2017). La actitud de los recursos humanos de las organizaciones ante la complejidad de las aplicaciones SaaS. Dos Algarves Multidiscip. J. 28, 87–103. doi: 10.18089/damej.2016.28.1.6
Palos-Sanchez, P. R. (2017). El cambio de las relaciones con el cliente a través de la adopción de APPS: estudio de las variables de influencia en M-Commerce. Rev. Espacios 38:38.
Peñarroja, V., Orengo, V., Zornoza, A., and Hernández, A. (2013). The effects of virtuality level on task-related collaborative behaviors: the mediating role of team trust. Comput. Hum. Behav. 29, 967–974. doi: 10.1016/j.chb.2012.12.020
Perrow, C. (1967). A framework for the comparative analysis of organizations. Am. Soc. Rev. 32, 194–208. doi: 10.2307/2091811
Piccoli, G., Powell, A., and Ives, B. (2004). Virtual teams: team control structure, work processes, and team effectiveness. Inf. Technol. People 17, 359–379. doi: 10.1108/09593840410570258
Pitagorsky, G. (2007). “Managing virtual teams for high performance,” in Paper Presented at PMI§Global Congress , (North America, Atlanta, GA: Project Management Institute).
Powell, A., Piccoli, G., and Ives, B. (2004). Virtual teams: a review of current literature and directions for future research. SIGMIS Database 35, 6–36. doi: 10.1145/968464.968467
Pridmore, J., and Phillips-Wren, G. (2011). Assessing decision making quality in face-to-face teams versus virtual teams in a virtual world. J. Decis. Syst. 20, 283–308. doi: 10.3166/jds.20.283-308
Purvanova, R. K., and Bono, J. E. (2009). Transformational leadership in context: Face-to-face and virtual teams. Leadersh. Q. 20, 343–357. doi: 10.1016/j.leaqua.2009.03.004
Rapp, A., Ahearne, M., Mathieu, J., and Rapp, T. (2010). Managing sales teams in a virtual environment. Int. J. Res. Mark. 27, 213–224.
Rashid, M., and Dar, J. (1994). Current managerial styles & effective managers. Manage. Serv. 38, 16–17.
Reinartz, W., Haenlein, M., and Henseler, J. (2009). An empirical comparison of the efficacy of covariance-based and variance-based SEM. Int. J. Res. Mark. 26, 332–344. doi: 10.1016/j.ijresmar.2009.08.001
Ribes-Giner, G., Perelló-Marin, M. R., and Pantoja-Diaz, O. (2017). Revisión sistemática de literatura de las variables clave del proceso de co-creación en las instituciones de educación superior. Tec. Empre. 11, 41–53. doi: 10.18845/te.v11i3.3365
Rico, R., and Cohen, S. G. (2005). Effects of task interdependence and type of communication on performance. J. Manage. Psychol. 20, 261–274. doi: 10.1108/02683940510589046
Saldaña Ramos, J. (2010). VTManager: Un Marco Metodológico Para la Mejora de la Gestión de Los Equipos de Desarrollo Software Global. Madrid: Universidad Carlos III de Madrid.
Salisbury, W. D., Carte, T. A., and Chidambaram, L. (2006). Cohesion in virtual teams: validating the perceived cohesion scale in a distributed setting. SIGMIS Database 37, 147–155. doi: 10.1145/1161345.1161362
Sánchez, P. R. P. (2017). Drivers and barriers of the cloud computing in SMEs: the position of the European union. Harv. Deusto Bus. Res. 6, 116–132.
Sarker, S., Sarker, S., and Schneider, C. (2009). Seeing remote team members as leaders: a study of US-Scandinavian teams. IEEE Trans. Prof. Commun. 52, 75–94. doi: 10.1109/TPC.2008.2007871
Schepers, J., de Jong, A., de Ruyter, K., and Wetzels, M. (2011). Fields of gold: perceived efficacy in virtual teams of field service employees. J. Service Res. 14, 372–389. doi: 10.1177/1094670511412354
Schweitzer, L., and Duxbury, L. (2010). Conceptualizing and measuring the virtuality of teams. Inf. Syst. J. 20, 267–295. doi: 10.1111/j.1365-2575.2009.00326.x
Shuffler, M. L., Wiese, C. W., Salas, E., and Burke, C. S. (2010). Leading one another across time and space: exploring shared leadership functions in virtual teams. Rev.Psicolog Trabajo Las Organ. 26, 3–17. doi: 10.5093/tr2010v26n1a1
Simons, T. L., and Peterson, R. S. (2000). Task conflict and relationship conflict in top management teams: the pivotal role of intragroup trust. J. Appl. Psychol. 85:102. doi: 10.1037/0021-9010.85.1.102
Spector, T. (2006). Does the sustainability movement sustain a sustainable design ethic for architecture? Environ. Ethics 28, 265–283. doi: 10.5840/enviroethics200628317
Subramanyam, V. (2013). Team cohesion between national youth and junior volley ball players: a comparative analysis. Int. J. Sports Sci. Fitness 3, 250–258.
Tan, C. K.\, Ramayah, T., Teoh, A. P., and Cheah, J.-H. (2019). Factors influencing virtual team performance in Malaysia. Kybernetes 48, 2065–2092. doi: 10.1108/K-01-2018-0031
Velicia-Martin, F., Cabrera-Sanchez, J.-P., Gil-Cordero, E., and Palos-Sanchez, P. R. (2021). Researching COVID-19 tracing app acceptance: incorporating theory from the technological acceptance model. PeerJ Comput. Sci. 7:e316. doi: 10.7717/peerj-cs.316
Warkentin, M., and Beranek, P. M. (1999). Training to improve virtual team communication. Inf. Syst. J. 9, 271–289. doi: 10.1046/j.1365-2575.1999.00065.x
Wei, L. H., Thurasamy, R., and Popa, S. (2018). Managing virtual teams for open innovation in Global Business Services industry. Manage. Decis. 56, 1285–1305. doi: 10.1108/MD-08-2017-0766
Werts, C. E., Linn, R. L., and Jöreskog, K. G. (1974). “Quantifying unmeasured variables,” in Measurement in the Social Sciences , ed. H. M. Blalock, (Chicago: Aldine Publishing Co), 270–292. doi: 10.4324/9781351329088-11
Whitford, T., and Moss, S. A. (2009). Transformational leadership in distributed work groups: the moderating role of follower regulatory focus and goal orientation. Commun. Res. 36, 810–837. doi: 10.1177/0093650209346800
Zúñiga Ramirez, C., Solano Cordero, J., and Bolaños Garita, R. (2016). Quantic trends in knowledge-based companies: a case analysis of a Costa Rican experience. Tec. Empresarial 10, 29–40. doi: 10.18845/te.v10i3.2938
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]
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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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Management Research News
ISSN : 0140-9174
Article publication date: 25 January 2008
This paper aims to extend knowledge about virtual teams and their advantages and disadvantages in a global business environment.
Design/methodology/approach
Based on a literature review and reported findings from interviews with experts and practitioners in the field, the paper has identified and discussed the advantages and problems associated with creating and managing virtual teams.
In today's competitive global economy, organizations capable of rapidly creating virtual teams of talented people can respond quickly to changing business environments. Capabilities of this type offer organizations a form of competitive advantage.
Originality/value
By identifying the advantages and problems associated with virtual teams, organizations will be better able to successfully establish and manage such teams.
- Virtual work
- Team management
- Cross‐cultural management
- International business
Bergiel, B.J. , Bergiel, E.B. and Balsmeier, P.W. (2008), "Nature of virtual teams: a summary of their advantages and disadvantages", Management Research News , Vol. 31 No. 2, pp. 99-110. https://doi.org/10.1108/01409170810846821
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Copyright © 2008, Emerald Group Publishing Limited
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49 Virtual Team Essay Topics
🏆 best essay topics on virtual team, 🎓 most interesting virtual team research titles, 💡 simple virtual team essay ideas.
- Communication Strategies for Virtual Teams
- Building Virtual Teams and Its Key Factors
- Virtual Teams’ Adaptation to the Conditions of the COVID-19 Pandemic
- Working in a Virtual Team, Multiculturalism
- Virtual Team Case Study. Communication Issue
- Virtual Team Management: Skills and Practices
- Cross-Cultural Management for Virtual Teams: Context, Theories and Critical Cultural Influences
- Effective Leadership in Global Virtual Teams
- Virtual Project Teams’ Advantages & Disadvantages
- Definition and Key Characteristics of Virtual Team
- The Benefits of Virtual Teams for Global Organizations
- Challenges of Managing Virtual Teams: How to Overcome Them
- Communication Strategies for Effective Virtual Team Collaboration
- The Role of Technology in Facilitating Virtual Teams
- Building Trust in Virtual Teams: Tips for Leaders
- Strategies for Managing Time Zones in Virtual Teams
- Understanding How to Foster Teamwork and Collaboration in a Virtual Team
- The Importance of Cultural Awareness in Global Virtual Teams
- Virtual Team Productivity: Tools and Techniques for Success
- Managing Remote Workload: Balancing Tasks in Virtual Teams
- Concept of Virtual Teams in Business Continuity During Crises
- Future of Work: How Virtual Teams Are Shaping Modern Organizations
- Explaining How to Onboard New Employees in a Virtual Team Environment
- Leadership Styles for Managing High-Performing Virtual Teams
- Virtual Teams vs. Traditional Teams: Differences/Similarities
- Aspects Employee Engagement in a Virtual Team
- The Impact of Virtual Teams on Organizational Culture
- Using Project Management Tools to Boost Virtual Team Efficiency
- Role of Virtual Team Building Activities in Enhancing Cohesion
- Techniques for Resolution Conflict in Virtual Teams
- Overview to Ensure Accountability in Virtual Teams
- Remote Leadership: Skills Needed to Lead a Successful Virtual Team
- Clear Communication in Virtual Team Success
- Employee Wellbeing in Virtual Teams: Managing Stress and Burnout
- Artificial Intelligence (AI) in Supporting Virtual Teams
- Strategies How Virtual Teams Can Enhance Work-Life Balance
- Remote Work Tools: Essential Software for Virtual Teams
- Considerations in Virtual Teams in Agile Work Environments
- Managing Diversity in Virtual Teams
- How to Ensure Data Security and Privacy in Virtual Teams
- Virtual Teams and the Gig Economy: The Rise of Freelance Collaboration
- Aspect of Cloud Computing in Virtual Team Collaboration
- The Importance of Flexibility and Adaptability in Virtual Teamwork
- Cross-Functional Virtual Teams: How to Manage Expertise Across Borders
- Effect of Virtual Teams on Employee Retention and Recruitment
- Time Zone Overlaps in Global Virtual Teams
- Role of Emotional Intelligence in Leading Virtual Teams
- Virtual Teams and Remote Innovation – Drive Creativity
- Concept to Managing Virtual Teams During Organizational Change
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These essay examples and topics on Virtual Team were carefully selected by the StudyCorgi editorial team. They meet our highest standards in terms of grammar, punctuation, style, and fact accuracy. Please ensure you properly reference the materials if you’re using them to write your assignment.
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Since research on virtual teams directed by transformational leadership is an ... Studies revealed superior sought-after competencies like relationship building in diverse management teams mixed by age, gender, and cultural ... Web of science use in published research and review papers 1997-2017: A selective, dynamic, cross-domain, content ...
Topic 3 research delves into the factors and challenges of communication in global virtual teams (GVTs), including cultural diversity, geographic distance, language barriers, communication media, trust, motivation, and conflict. Some papers offer insights into how culturally diverse VTs can effectively address these issues [73 - 77].
This paper attempts to explain the role of vital elements like trust, information sharing and communication, in building virtual teams. This study strives towards developing a set of factors using SEM that can be used by managers of virtual teams for establishing an efficacious relationship amongst the members. Previous.
This review summarizes empirical research on the management of virtual teams, i.e., distributed work teams whose members predominantly communicate and coordinate their work via electronic media (e-mail, telephone, video-conference, etc.). Instead of considering virtual teams as qualitatively distinct from conventional teams, the degree of ...
Björn Niehaves. University of Siegen, Germany. bj [email protected]. Abstract. With the outbreak of COVID- 19, many organizations. are facing the challenge of switching to virtual work ...
The article also examines the challenges of remote work and virtual team management, including communication barriers, building trust, time zone differences, and ensuring accountability and ...
To address rapidly developing markets, businesses are implementing changes in leadership structures, work systems, and technology adoption. Human resource development (HRD) and virtual HRD (VHRD) practitioners and researchers must draw on best practices from previous research regarding virtual teams to help meet organizational needs and changes.
Creativity and Innovation Management, a management research journal, explores strategies to support creative potential & embed it into innovative business development. Virtual teams are gaining increasing momentum in contemporary organizations. Although it is becoming clear that virtual teams will play a major role in shaping the future of work ...
Virtual teams (VTs) are groups of people who work interdependently with shared purpose across space, time, and organization boundaries, using technology to communicate and collaborate. This literature review examined the status of the published research on VTs functioning to identify the main factors impacting their performance. Our main findings are the conceptualization of a multi-level ...
Journal of Leadership Studies publishes leadership research and theoretical papers bridging scholarship & practice, exploring the primacy of leadership's role. Over the years, an explosive growth in the use of virtual teams in organizations has been noticed. ... The purpose of the paper is to try to comprehend how virtual teams work better, by ...
In contrast, using 109 samples of non-organizational teams (5620 teams), we show that virtuality is a significant negative input to team effectiveness. We also meta-analytically assess the issue of results generalizability from non-organizational to organizational settings, and find that overall, results from non-organizational studies largely ...
The last 10 years of empirical work around 10 main themes: research design, team inputs, team virtuality, technology, globalization, leadership, mediators and moderators, trust, outcomes, and ways to enhance VT success are organized. Ten years ago, Martins, Gilson, and Maynard reviewed the emerging virtual team (VT) literature. Given the proliferation of new communication technologies and the ...
Modern developments in technology have changed the way we socialize, communicate and work. Globalization, Information and Communication Technologies, digital culture and the increase in the amount of technology available for online communication mean that more organizations are implementing virtual teams. The growth in the use of virtual teams in organizations has incited researchers to ...
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. ... Virtual teams research: 10 Years, 10 themes, and 10 opportunities. J.
The systematic review of literature proposed by Ramey and Rao [1] and enhanced by Pulsiri and. Thesenvitz [2] was used to examine the Scopus and W eb of Science databases to identify the theories ...
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 ...
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.,A data set of 107 relevant papers on ...
Virtual work is the new normal, with employees working from dispersed locations and interacting using computer-mediated communication. Despite the growth in virtual work research, it has tended to occur in siloes focused on different types of virtual work (e.g., virtual teams and telecommuting) that are grounded in different research traditions. This limits opportunities to leverage research ...
However, the foundations and theoretical development of virtual team research remain unclear. We propose that an important way to move forward is to accelerate the process of theorizing and theory appropriation. This article presents an in-depth analysis of the current state of the art of theory application and development in virtual team research.
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. ... Therefore, software companies can use it as a theoretical framework when preparing their human resources and Virtual Teams management policies.
Abstract. Virtual team management is the ability to organize and coordinate with effect a group whose members are not in the same location or time zone, and may not even work for the organization ...
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].
This paper aims to extend knowledge about virtual teams and their advantages and disadvantages in a global business environment. Design/methodology/approach Based on a literature review and reported findings from interviews with experts and practitioners in the field, the paper has identified and discussed the advantages and problems associated ...
Looking for the best Virtual Team topic for your essay or research? 💡 StudyCorgi has plenty of fresh and unique titles available for free. 👍 Check out this page! ... Using Project Management Tools to Boost Virtual Team Efficiency ... Building Activities in Enhancing Cohesion. 💡 Simple Virtual Team Essay Ideas. On-time delivery! Get ...