Introduction

• Online collaboration, including across international borders, is becoming ubiquitous. Most white-collar workers at least occasionally complete projects in global virtual teams (GVTs).
• Thus, understanding what affects GVT dynamics and performance is important.
• Much research in this area, from exploration of the effects of team composition, to team leadership, to team communication channels on GVT dynamics and performance.
• The present study builds upon a body of literature on the role of communication and collaboration tools in GVTs.
• Up until about a decade ago, most online collaboration was limited to emails, phone, and video conferencing (i.e., Skype)
• However, in the past few years, tools dedicated to online collaboration (distinct from communication) emerged. Tools that are not so much for communication as in information exchange, but collaboration as in document management, co-editing, and general project management.
• The simplest form of project collaboration is email attachment. It’s been around for close to 30 years and will likely remain around for some time due to the fact that close to 100 % of office workers have an email address, its simplicity, and habit.
• More advanced forms of document co-management are cloud document storing and sharing services, such as Dropbox and OneDrive, and multi-user document sharing and co-editing services such as Google Docs.
• There are also more comprehensive project management solutions such as Base Camp which incorporate features of document sharing, work log, email, and more.
• The present study explores how the choice of the collaboration tools affects GVT dynamics and performance.
• If there is an effect, the implications for GVT training, work design, and management are huge.
• In the remainder of the paper, we first provide a classification of the collaboration tools and place them on a parallelism scale. We then propose a series hypotheses regarding the choice of the collaboration tool use in GVTs, then detail our research design and methodology, provide the results of our study. We conclude with a discussion of implications of our findings for GVT development and management.

 

Theory

 

Classification of Collaboration Tools on Parallelism

• The online collaboration tools can be classified and categorized in many different ways.
• The present study focuses on the tools “parallelism”, that is to what degree the tool allows for a simultaneous multi-user document access and co-editing.
• Email attachments would rate the lowest on the parallelism scale. It allows for only sequential access to the document. The document can be edited by one member of the team at one time only. Until it’s processed and emailed to the team members as attachments, other team members cannot see what is going with the document and cannot make changes to it. Moreover, collaboration via email attachments tends to be not only very slow, but also result in multiple copies of the document. If multiple members of the team try to work with the file, the number of copies quickly grows, often conflicting copies are created, it is not always easy to figure out which copy is the latest and merge conflicting copies, which only further slows team’s progress. This results in a work for that is far from parallel: it is often slower than sequential because the team often has to go in loops, backtracking to figure out which is the latest document copy and merging conflicting copies.
• Dropbox and other cloud document sharing services are in the middle of the parallelism scale. They offer the huge advantage of everyone having access to the same single copy of the document stored in a shared cloud folder. They usually do not allow simultaneous document co-editing, but make it easy to see in real time if and who is working on the document at any given time. They greatly improve speed and workflow compared to email attachment, although they do not offer true parallel multi-user document editing.
• Google Docs scores highest on the parallelism scale. It allows the same document to be simultaneously open and edited by multiple GVT members. Team members can see in real time changes made by other team members. Moreover, it allows for text, voice, and video chat for the added level of richness of collaboration.
• Thus, with respect to parallelism, online collaboration tools can be categorized as the following:
  • Email attachment: no parallelism
  • Dropbox and similar cloud document storage and sharing tools: some parallelism
  • Google Docs and similar collaboration tools: full parallelism

 

Hypotheses:

• H0: It may be a good idea to explore what predicts the team’s use of the different tools. More likely than not, this is rather random. Somebody on the team suggests, others support. However it could be that:
  • Older teams are more likely to use email only (either average team age, or minimum team age)
  • Larger teams are more likely to use parallel tools
  • Diversity, MBA/UG, skills (as per the Readiness Test score)?
    • Readiness Test is especially promising. If we are finding a positive effect of parallelism, and then also finding that teams that are more prepared (higher Readiness Test score) are more likely to use parallel tools, this is direct implications for selections and training.

 

• H1: Teams that use collaboration tools that offer more parallelism will show a lower degree of team member performance variance.
  • More parallelism makes individual effort more visible and performance tracking easier
  • As a result, it’s harder to shirk. So there is less chance of free-riding (social loafing)
  • Everyone makes a more even level of contribution to the team, thus the variance in individual performance will be lower.
• H2: Teams that use collaboration tools that offer more parallelism will show a more positive team dynamics: team member satisfaction, team identification, project satisfaction, etc.
  • More even contribution (actual and visible) positively affects team member satisfaction and attitudes.
  • As a result, use of high-parallelism collaboration tools improves team member satisfaction, team identification, project satisfaction, etc.
• H3: Teams that use collaboration tools that offer more parallelism will show an overall higher performance level
  • Higher satisfaction with the project and team leads to higher effect and performance.
  • As a result, team members participate more actively and produce work of higher quality.
• H4: The effect of parallelism on team performance and dynamics will be moderated by the team size and diversity so that the positive effect of parallelism will be stronger in larger and more culturally diverse teams.

 

 

Method

Study context

• X-Culture was used a research platform for the study.
• The X-Culture project (X-Culture.org) was used as the research platform for the present study. X-Culture is a large-scale international experiential learning project that involves over 3,500 MBA and business students from 100 universities from 40 countries on six continents every semester. The students are placed in global virtual teams of about seven, each student coming from a different country. Working with people from around the globe and dealing with cultural differences, time-zone dispersion, and global communication challenges, the teams complete a consulting project for a multi-national company.
• The X-Culture project is an 8-week structured program in which participants studying international business throughout the world are assigned to virtual teams of 5 to 7 people, with each team member from a different country. The teams are instructed to develop a full business plan, with the goals, constraints, and commitments laid out at the beginning of the program, for an international venture. Each team works on a different plan, some of which at the request of real customers and enterprises that support the program.
• The project environment closely emulates the one in which the corporate global virtual teams operate. They both have a well-defined measurable mandate, and have to conduct business long-distance, face internal cultural differences, operate in different time zones, and to be multilingual (with English as the business language). The team members do not know each other, yet their individual performance is partially measured by the output of a team that they do not know and nor select. Peer evaluations of the performance of each team member are recorded (direct measures on contribution, absenteeism, communication skills, participation, etc.) and the quality of the entire team’s output is evaluated and scored by a committee of experts.
• Problems with using student samples in business research are widely known. This convenience-sampling approach has been justifiably criticized because the findings obtained using student samples may not generalize to the real-world workplace environment. The lack of generalizability is a result of (1) the different student demographics and (2) differences in the work design.
• The students are typically younger than their corporate counterparts. Generally, this presents no threat to validity of the findings, but sometimes age, work experience, or marital status may be believed to moderate the relationship of interest and if that is the case, the younger age of student samples may be of a concern. In other words, if the focus of the study is on general attitudes, personality, or reactions that are likely to be universal across different representatives of the general public, the younger age of the student-sample study participants should not present a problem. However, if the constructs in question are believed to morph as one matures and gains work experience, use of student samples may indeed present a problem.
• The work design differences are a usually a much bigger concern. A typical student-based study is usually limited to a simple in-class experiment. The student team members lack the interdependence commonly observed in organizations. The completion of the task is usually quick, often taking only minutes and rarely longer than a class session. The cost of failure and compensation are not a factor at all, which changes the motivation and incentive structure. And if culture is part of the model, cultural diversity in student samples is often “artificial” in the sense that it is either induced through priming (c.f. Oyserman, Kemmelmeier, & Coon, 2002), or even if the students come from different countries, they tend to be acculturated and adjusted to the host culture. This would be particularly of a concern if performance is a key variable of the model, or is used to validate the predictive validity of an instrument with respect to its effect on team dynamics and performance.
• A careful inspection of the subject of the present study suggest that our sample characteristics present no major threats to validity of our findings. First, the demographics of the present project participants was not meaningfully different from the demographics of their corporate counterparts. About half of the participants were MBA and EMBA students, and the rest were business students in their last or second last year of studies. The vast majority of the participants had at least some work experience, and many were employed at the time of the project. Many participants reported they had their own businesses or held managerial positions. Most project participants aged 21-28, with an average of about 25 years, and about 16% of the participants in their 30 and 40s. These are the people who either already are or will be organizational employees in a year or so and will comprise the core of business organizations.
• For all purposes, our sample was every bit as good, or possibly even better, than what could be obtained from corporate organizations. First, the cross-cultural international settings were very real. The study participants worked in international virtual teams, each composed of about seven people with 5.2 different countries represented on each team (sometimes two team members were from the same country while the rest of the team member each came from a different country). The geographic and time-zone dispersion, cultural and language differences were real.
• Second, the study task and environment were designed to resemble the corporate world as closely as possible. The team member interacted daily during 8-9 weeks, which is a typical project length in the corporate world. Once the students enrolled in the course that participated in the project, they were required to take part in the project. The team assignment was random and students had no choice over the countries represented on their teams. This is similar to how it works in the corporate world: accepting a job offer is voluntary, but once in a job, one has little choice as to what projects to work on and with whom.
• The project involved development of a solution to real-life business challenges presented by real-life companies. The task involved market research, market entry plan development, and product design. The project was supervised by instructors with rich business consulting experience and managed as a regular business consulting project.
• Just like in the corporate world, the teams were given significant autonomy in terms of the extent and type of communication methods. However, all participants were introduced to and were encouraged to use free collaboration tools, such as email, voice and video conferencing tools (e.g., Skype), document and collaboration platforms (e.g., Google Docs and Dropbox), and social media (e.g., Facebook and Google +), similar to what is commonly used in a corporate environment.
• The stakes were very high and the project was effectively a temporary employment for the client organization. First, the project accounted for 20 to 50% of the course grade. A failure on the project usually meant a failure in the course, with all resulting negative effects on future career prospects. The members of the best teams were invited project participants symposiums held once a year. Most attended received travel stipends. Additionally, organizations offered post-market commission, as well as prospects of internships and job offers. So from every angle, the project settings and work design were not different from those in organizations and the threat that the findings of the present study would not generalize to the corporate employee population is extremely small.
• Most important, the advantages of the large international sample from the X-Culture project probably greatly outweighed the possible disadvantages due to marginally younger sample demographics. There is certainly a tradeoff between a smaller sample of “real” workplace GVTs (usually a one-team case study and hardly ever exceeding a N=10) and literally a hundred times as many real “global” and “virtual” teams working on a standardized business consulting project, but the teams members being a little younger than their corporate counterparts. Despite certain threats to generalizability of the findings, the latter option is a viable and likely superior alternative.

 

Sample

• N of students
• N of teams
• Number of countries/universities
• Min, max and Average age
• Min, max and Average team size
• MBA vs. UG
• Min, max and average number of countries per team

 

Results

 

Basic stats

• Descriptive Stats: means, mins, maxs, SDs and zero-order correlations.
• Parnellism: a table of teams showing % of teams using:

 

	Using at least occasionally	Using regularly	Using exclusively
Email attachments	100	80	50
Dropbox	30	20	8
Google Docs	10	5	4

Hypothesis tests

 

 

 

Conclusions