virtual team meetings: an analysis of communication and context

Computers in

Computers in Human Behavior 23 (2007) 2558–2580

Human Behavior

www.elsevier.com/locate/comphumbeh

Virtual team meetings: An analysisof communication and context

A.H. Anderson a,*, R. McEwan b, J. Bal c, J. Carletta d

a School of Computing, University of Dundee, Dundee DD1 4HN, UKb Department of Psychology, University of Glasgow, Glasgow G12 8QB, UK

c Warwick Manufacturing Group, University of Warwick, Coventry CV4 7AL, UKd Informatics Division, University of Edinburgh, Edinburgh EH8 9LW, UK

Available online 20 February 2007

Abstract

We report a simulation study of virtual team meetings. Participants role-played companies collab-orating on a design problem while supported by a range of IT tools, such as videoconferencing andshared applications. Meetings were analysed to investigate how sharing computing facilities, operat-ing the technology, and company status, influenced communications. Significantly more talkoccurred in larger teams where participants shared I.T. facilities BUT this extra talk was restrictedto talk within a single location. No extra talk was shared across the virtual team via the communi-cations link. Where facilities were shared, technology controllers dominated cross-site talk. Toencourage free communication across distributed virtual teams we recommend providing each par-ticipant with their own communications facility even if this is technologically less advanced than iftechnology support were shared.� 2007 Elsevier Ltd. All rights reserved.

Keywords: Virtual teams; Distributed group working; Communication analyses; Multimedia communications

1. Introduction

New developments in information and communication technologies are predicted tohave significant impacts on the workplace. The ready availability of relatively low cost

0747-5632/$ - see front matter � 2007 Elsevier Ltd. All rights reserved.

doi:10.1016/j.chb.2007.01.001

* Corresponding author. Tel.: +44 0 1382 386610; fax: +44 0 1382 386611.E-mail address: [email protected] (A.H. Anderson).

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A.H. Anderson et al. / Computers in Human Behavior 23 (2007) 2558–2580 2559

access to higher bandwidth connectivity means that new forms of remote working areincreasingly popular. There has been much hype around concepts such as the ‘death of dis-tance’ Cairncross (1997). Even if such claims are exaggerated, companies are investigatingnew styles of organizations and ways of working. Many of these developments exploit thepotential of communication and information technologies.

Martins, Gilson, and Maynard (2004) in a major review of the literature on virtualteams, conclude that ‘with rare exceptions all organizational teams are virtual to someextent.’ The term ‘virtual team’ is used to cover a wide range of activities and forms oftechnology-supported working. Kirkman and Mathieu (2007) propose that the term ‘teamvirtuality’ could be more useful as it could be used to describe ‘the extent to which teammembers use virtual tools to coordinate and execute team processes, the amount of infor-mation value provided by such tools and the synchronicity of team member virtualinteractions’.

We report a study on one aspect of such new ways of working: the use of virtual teamworking in the supply chain. The study we describe in this paper is a simulation study ofengineers engaged in a highly virtual work. The teams of engineers took part in a lab basedstudy under comparable conditions, all tackling the same real engineering problem sup-ported by multimedia technologies for distributed synchronous collaboration. We carriedout detailed quantitative analyses of the way the teams communicated when the teams andtheir technology support, were configured into two different ways.

This study seeks to address some of the gaps in the existing extensive literature on vir-tual teams. As reviews of this literature such as Driskell, Radtke, and Salas (2003) andMartins et al. (2004), point out the majority of the studies that have been carried outuse, student participants supported by text-based communication. The smaller numberof studies which have been carried out on workplace virtual teams have again often beenon teams which rely on asynchronous email communication. Martins et al. (2004) con-clude their extensive review by outlining future research challenges, including ‘a need toshift away from seeking to compare virtual teams to face-to-face ones, to an examinationof how the extent of virtualness affects virtual team functioning. . . It is imperative, though,that empirical research move out of laboratory settings and into the field . . .asking andanswering questions that cannot be adequately tested in a laboratory setting. Some inter-esting questions for future research include: What are the implications of organizationalpower differentials among VT members?’

In this paper we attempt to do just this by studying different forms of technology sup-port for virtual team working in the supply chain, a particularly relevant and challengingorganizational context for distributed collaboration. So as Martins et al. (2004) recom-mend we are not comparing virtual team working with face-to-face interactions, ratherwe are exploring the impact of different ways of supporting distributed work in a closeapproximation of real working conditions in cross organizational collaboration.

A supply chain is a group of companies, so in manufacturing this starts at the top ofthe chain with the original equipment manufacturer (OEM) such as a car manufacturer.Then at the next level there are first tier suppliers, who are companies that supply majorcomponents of the product such as braking systems. At the next level down the chainare second tier suppliers who are manufacturers of sub-components (e.g. producers ofbrake shoes). In a supply chain, individuals from different companies have to communi-cate. As product development becomes more complex, they also have to collaboratemore closely than in the past. These kinds of collaborations almost always involve

2560 A.H. Anderson et al. / Computers in Human Behavior 23 (2007) 2558–2580

individuals from different locations, so virtual team working supported by IT, offers con-siderable potential benefits. To reiterate, here we use virtual team working to mean syn-chronous work supported by information and communication technologies. In the studyreported in this paper this involved video conferencing tools, shared white boards andshared access to other forms of IT support for active collaborative working on jointtasks.

Virtual teaming has been very enthusiastically advocated by many authors in manage-ment and business such as Grenier and Metes (1995), Snow, Snell, and Davison (1996),and Lipnack and Stamps (1997). More cautious or negative views have also been voicedby authors such as De Meyer (1991), Nohria and Eccles (1992), Handy (1995) and mostnotably Olson and Olson (2000). One important dimension to virtual team working iscommunication. This provides one method for evaluating the effectiveness of virtual teamworking. Good communication flow within organizations is considered to be important incomplex business environments (e.g. Innovation in Manufacturing Industry, 1991). Goodcommunication among team members has also been reported to be important if teamworking is to operate successfully. Communicative difficulties in traditional and virtualteams have been found to relate to poor performance (e.g. Carletta, Garrod, & Fraser-Krauss, 1998; Mathieu, Heffner, Goodwin, Salas, & Cannon-Bowers, 2000; Thompson& Couvert, 2003). If companies are to benefit from introducing virtual team working thengood communication seems desirable.

Many of the acknowledged challenges of effective virtual team working, focus on ensur-ing good communication among all members of the distributed team. For example, Jar-venpaa and Leidner (1999) found that regular and timely communication feedback waskey to building trust and commitment in distributed teams. Kayworth and Leidner(2000) from studies of virtual teams where members were distributed around the world,concluded that frequent ongoing communication was essential for success. Blackburn,Furst, and Rosen (2003) found that developing a common sense of purpose was more dif-ficult in virtual teams as there was less intensive communication and interaction. Richercommunication media are held to offer advantages for virtual team working, and authorssuch as Kayworth and Leidner (2000) are optimistic that the wider availability of thesemedia will overcome many of the communication problems of virtual teams. There is how-ever, relatively little detailed empirical evidence on the impact of different forms of multi-media communication on patterns of communication in the workplace.

A few researchers have reported studies of virtual teams in action, using multimediasupport for their synchronous collaborations. These studies of virtual team meetingsamong work groups, have shown some communicative differences in style. Turn exchangeswere different, with lengthier contributions and more formal handovers in virtual meetings(O’Conaill, Whittaker, & Wilbur, 1993). Technology support led to shorter meetings thatwere more problem-centered interactions than face-to-face workplace interactions(O’Conaill et al., 1993; Tang & Isaacs, 1993; Tang, Isaacs, & Rua, 1994). There are agreater number of empirical studies of virtual meetings among participants in lab-basedstudies, although most of these use text based communications, a few do report studiesof technology supported spoken interactions such as video conferences. For example Sel-len (1995) reported few differences in the communications among users of very differentvideo communication systems, Olson, Olson, and Meader (1995), and Doherty-Sneddonet al. (1997) both reported that video supported teams performed as well as those inface-to-face meetings though distributed teams had to spend more time in clarifying their


contributions to the meetings. Anderson et al. (1999) also reported equally successful out-comes in distributed video-linked groups but more difficulties in handling smooth transi-tions between speakers. Sanford, Anderson, and Mullin (2004) reported the impact ofdifferent configurations of audio link on the communication patterns in videoconferences,with surprising benefits for apparently more artificial ‘click to speak’ systems over openchannel communication. For a review of experimental studies of virtual teams see Driskellet al. (2003).

The supply chain provides a fascinating environment in which to investigate the impactsof technology-supported working. This environment highlights the complexities of thework place with its networks of social and organizational relationships between individu-als and companies. In the past a manufacturing company (an OEM) would have a dom-inant role with its suppliers, determining the specifications for requirements and waitingfor suppliers to compete for orders to supply the required components. Now complexproducts are designed much more collaboratively with the suppliers being involved inthe design process. The production of a new car for example involves different companiesin the supply chain acting more as partners in a joint manufacturing exercise. The intro-duction of virtual team working in theory fits well with these larger organizationalchanges. It is not clear in practice how traditional status and hierarchical relationships willinfluence the nature of communication in virtual meetings.

Studies of communication in the workplace have shown that higher status individualstend to dominate face-to-face business meetings (e.g. Carletta et al., 1998). One of the fre-quently cited advantages of early research on email communications within organizations,was the equalizing effect, with studies showing that email reduced the influence of statusand allow freer and more equal patterns of communication, (Dubrovsky, Kiesler, & Set-hna, 1991; Kiesler & Sproull, 1992; Sproull & Kiesler, 1986). In contrast, Saunders,Robey, and Vaverek (1994) report that status differentials were maintained in text-basedconferences. For ‘richer’ communication media (Daft & Lengel, 1984) we know much lessabout how status and communication technologies interact. In a study of audio conferenc-ing in the workplace, France, Anderson, and Gardner (2001) found that effects of statuson communication were considerably larger in audio conferences than face-to-face meet-ings. In this paper we explore if status within the supply chain impacts upon communica-tion in virtual team meetings and if multimedia support technologies can be implementedto overcome any such influences.

In a previous study of virtual teams in the work place we utilized several research meth-ods and data gathering techniques, including, interviews, questionnaires, and observationsof virtual team meetings (Carletta, Anderson, & McEwan, 2000). As is common in work-place studies we observed many fascinating examples of virtual team behaviour and com-munication, but our sample was fairly small and the variation between virtual teamsmeant that our analyses were not conclusive. From our observations of two virtual teamsin the workplace it appeared however, that the way in which the support technologies wereimplemented affected communication among the virtual team members.

One of the potential advantages of virtual team working is the ability rapidly to recruitadditional members with relevant expertise (e.g Lipnack & Stamps, 1997). When the needto travel and commit to face-to-face interactions is removed, larger virtual teams perhapswith a more fluid membership, become a viable economic option for organizations. In ourworkplace observations of virtual teams, the ability to involve and receive input from awider set of individuals, was perceived as a potential benefit by companies. So virtual


teams may involve a larger number of members than traditional co-located teams. Howcan the technologies be configured to support teams with larger numbers and an evolvingmembership? There are two potential solutions. The first is to equip each individual withtheir own set of multimedia support tools, for communication and collaborative designing,etc. This of course has certain financial and organizational implications, in the time andresources needed to support a variety of computer work stations with high bandwidth con-nectivity and a set of multi media collaborative work tools. The second is to have severalteam members share specially equipped computers.

In this study we compare the impact of these two configurations on the communicationprocesses in virtual teams. The need to share facilities of course only arises when the vir-tual team grows beyond a certain size, so the comparison of necessity conflates the sharingof the equipment with the size of the team. The issue we wished to explore is whether thepresence of extra team members does provide benefits to the team, notably in terms of theflow of ideas and communication, when these extra team members have to share the vir-tual team technologies.

The literature on group size and technology is inconclusive. Some studies suggest that theuse of technologies (again usually text based communications) can overcome the problemsnoted with larger face-to-face problem solving groups where ideas can be blocked. So in vir-tual teams in contrast to face-to-face teams, more ideas have been recorded as the size of thegroup grows (e.g. Gallupe et al., 1992). When richer communication media are used the pic-ture can be rather different, Riopelle et al. (2003) found that larger groups had more diffi-culties communicating than smaller groups when using audio conferencing. Anderson(2006) found that even an increase from 2 to 3 members increased the communicative effortrequired to achieve task success, in both face-to-face and video conference interactions.

In our workplace observations of virtual teams (Carletta et al., 2000) we felt that teamsdid not always maximize the benefits of having extra members with additional expertisebecause of the way the technology support was implemented. For example, we observeda virtual team where the members convened a relatively lengthy meeting with several mem-bers at each site sharing the communications technology on a single work station. In thisvirtual meeting the communication among the virtual team members seemed less thanoptimum.

We found that there was little free interaction across the communication link, andinstead this vital cross-site communication was directed through a single team memberin each company – the one who was operating the technology. Even when informationwas being exchanged between two people at different locations who were not operatingthe technology, communication appeared to be ‘squeezed’ through the people at the key-boards. These individuals dominated the conversation between sites. This was not becauseof technology limitations as the technology supported spoken conversation and each teammember could easily speak to colleagues at the other site. In practice this rarely happened.The person who controlled the computer interfaces who seemed to become a de facto com-pany spokesman.

In contrast we observed a virtual team that used the technology to have shorter meet-ings, with only one participant at a single workstation. This technological configurationseemed to elicit freer communication. In addition the status of the companies involvedappeared to impact on the process of the virtual team meeting and its communication,with participants from the OEM seeming to have a dominant role in the virtual teammeetings.


These observations suggested that technologies may be implemented in the workplacein ways that overturn the potential advantages of communications technology to supportfree communication across the team. This could have serious consequences. Given the sizeof the field study these conclusions were only tentative, but as the issue seemed of potentialimportance we decided to explore it more fully. We designed a study to test these conceptsin a lab simulation with a larger number of participants. We investigated how the form ofvirtual team implementation impacted on communications across the team. We were par-ticularly concerned with how the sharing of facilities influenced communication.

To do so we also had to address one of the methodological challenges of studying theimpact of the introduction of new forms of computer supported activities. Observationalstudies in the work place provide insights about the impact of computers in real organiza-tional settings. The richness of such contexts means that there is little or no control overthe people or behaviors observed. One virtual team meeting will differ from another on awide range of dimensions, such as the topics being discussed in the meetings, the length ofthe meeting, the experience of the team members, the organizational and social relation-ships between them, and the way the computer technologies have been implemented. Thismeans it is very difficult to interpret the causes of behavior that are observed during a vir-tual meeting.

Laboratory studies of computer-supported interactions, offer the advantages of carefulcontrol of a number of relevant variables, and thus repeated observations of meetings onidentical topics in identical situations. The trade-off for these advantages is that the par-ticipants are usually unfamiliar with one another. Participants are also often tackling sim-ple and artificial tasks about which they have no expertise and so may have little realengagement in the task.

In the study reported here we attempted to capture some of the advantages of bothtypes of research. We used what we called a ‘simulation study’ methodology. We recruitedparticipants with relevant real world expertise to play the roles of members of a virtualsupply chain team solving a problem. We used a real engineering problem that hademerged in some of our work place studies. This was a complex and engaging problemwith no one simple solution. The same problem however was presented to all the distrib-uted teams in our study who had equal time to meet and to complete the task. The teamsall had access to the same background information and their computer configurationswere controlled. The focus of our research was on how the technology configurationsinfluenced patterns of communication.

We focus on communication for a number of reasons for this. First we believe that care-ful analysis of the communication process, allows us to obtain a rather rich and detailedpicture of the virtual interaction, in ways which simple questionnaire responses or singleperformance measures do not. Secondly there is a fairly well established set of findingson the impacts of various forms of technology support which shows that participants showconsiderable perseverance and adaptability and will often complete tasks successfullyusing a wide variety of communication media. It is the analysis of the associated commu-nication that often provides insights into how easy or difficult achieving this outcome hasbeen, depending on the available communication facilities. These patterns have beenshown from the seminal work of Chapanis and colleagues onwards (e.g. Anderson,2006; Anderson et al., 1997; Chapanis, 1988; Sellen, 1995).

From our observations in the field, and the existing virtual team literature, we drew upthe following experimental hypotheses:


H1: Communication across a distributed virtual team, will differ when members share acommunications facility compared to when each has his or her own.H1A: Virtual teams with more members, even if they have to share a communicationfacility, should benefit in terms of the amount of communication and ideas exchangedacross the virtual team.H2: When virtual teams share communications facilities, the individuals who controlthe computer interface will contribute more cross-site talk than other team members.This effect will be restricted to such cross-site interactions and so will not just arise fromthe general dominance or loquacity of such individuals.H3: Communication will be influenced by the status of organizations within the supplychain.

2. Method

2.1. Participants

A total of 70 participants (all male) were recruited and randomly allocated to theshared facility or individual control condition of the study. All teams were virtual, thatis they collaborated with colleagues at a different location. In the shared facility condi-tion there were 52 participants who formed nine distributed teams of 4–7 individuals,with 2–4 individuals at each company site. This configurations, with larger teams withseveral members at each computer, is the experimental analogue of what we observedin the workplace. Larger virtual teams often involve sharing facilities. Here we willexplore the extent to which these larger teams lead to more communication across thedifferent locations.

In the individual control condition there were 18 participants who formed six distrib-uted teams of three individuals, with one person at each company site. Within each con-dition the participants were randomly assigned to role-play team members from differentcompanies within the supply chain. For the shared facility condition, participants wereassigned to OEM or 1st tier supplier, whilst for the individual control condition the par-ticipants were assigned to OEM, 1st tier and 2nd tier suppliers. The study thus is a com-parison of different forms of technology support for distributed team working.

The vast majority of participants had industrial experience and almost all wereemployed (92%). The remainder were engineering doctoral students. All participantshad a minimum of 1-year industrial experience in manufacturing, 50% had up to 5 yearsexperience, 32% had between 6 and 15 years experience and 18% had over 20 years expe-rience. Many of the participants had industrial experience similar to the participants in ourworkplace studies. All participants were very familiar with supply chain relationships.From the observations of the research team, several of whom had extensive industrialexperience, the participants role-played these companies very readily and convincingly.Very few participants had any experience of video conferencing before taking part in thisresearch though all were competent computer users. Familiarity among the team memberswas mixed. The majority of team members in both conditions knew all or most of the oth-ers in their teams. In each condition, a few participants were not familiar with their team-mates. This mixture was quite characteristic of the distributed virtual teams we hadobserved in industry.


2.2. Technology

In this study we used TEAM technology*, which provides rich computer support forcollaborative working. The facilities include video-conferencing, a shared whiteboard,and shared web-based product libraries. The interface controls are largely point-and-click.The technology supports spoken interaction among the team.

In the shared control condition, both sites had technology with identical capabilities –namely full duplex audio, two way video (via a moveable camera), shared whiteboardfacilities and a web-based data base.

In the individual control condition, the OEM and the 1st tier supplier had identicalcapabilities, and these were the same as in the shared control condition, namely full duplexaudio, two way video (via a moveable camera), shared whiteboard facilities and a web-based data base.

The facilities available at the third location, where the participants were in the roleof the 2nd tier supplier were less sophisticated. Transmission and reception of audiowas half duplex (i.e. ‘click to speak’), and was of poorer quality compared to theOEM and 1st tier supplier. This kind of audio configuration has been shown to haveadvantages to participants to communication when facilities are restricted, as speakersadjust their communication style, and do not expect to be able to contribute just asthey would in a face-to-face setting (Sanford et al., 2004). No video was available tothese participants, though. whiteboard and the web-based data base facilities werethe same.

This mirrored the context of a 2nd tier supplier in real life, as they are frequently lesstechnologically sophisticated than 1st tier suppliers and OEMs. As in real life, the variableof low status was associated with other pertinent variables, in this case lack of access tosophisticated technology, thus this ‘experimental confound’ is a part of the simulationof the work place.

2.3. Task

The scenario used in this study was based on a real life event between an automotiveOEM and its suppliers. The event centred around a failed steering gear assembly whichhad previously been supplied to an OEM by a 1st tier supplier to the OEM’s specifications.During routine tests in a hot climate overseas, the seals in the system had cracked andfailed and the oil had burnt. This had been caused by a design fault in the assembly thatonly became apparent under hot climate conditions. The problem required both a short-term fix to keep the costly test program on schedule, and secondly, a long-term solution topermanently prevent the overheating.

The desk top conferencing capabilities provide the virtual team with audio, video andshared whiteboard facilities which allow them to share a range of data sources. Theseinclude text based test reports, spread sheets containing information on alternative sealand oil materials and photographs of the relevant parts of the assembly which can beannotated to explore potential locations for the heat shield. The task consisted of the fol-lowing components: diagnosis of the problem; development of short-term solution; devel-opment of long-term solution; timing; cost liability.

In order to solve both problems, the groups needed to access the appropriate datasources, identify relevant data and share both text based data and visual images, i.e.


camera images or photographs. It was thus a highly interactive, complex problem solvingtask requiring real collaborative work.

2.4. Procedure

Each session lasted approximately 1.5 h. Participants were orientated to the idea of vir-tual team working in a 5 min introduction. They were then split into groups (or individualsfor the individual control condition) and randomly assigned to their supply chain roles ofOEM and 1st tier Supplier (shared control condition) or OEM, 1st tier Supplier and 2ndtier Supplier (individual control condition). They were then taken to their separate sites toreceive 20 min of technology training.

Participants were given written instructions that outlined the problem scenario and indi-cated the various information sources which would be available on the computer to helpthem to reach a solution. Appropriate information was available on each company’s com-puter that they could share with the whole team as they saw fit. Given the participants’familiarity with supply chain relations, this caused no difficulties. In the individual controlcondition, separate information was made accessible to OEM, 1st tier and 2nd tier suppliersfor them to share as they decided. In the shared control condition, the information distrib-uted was the same as in the individual condition for the OEM, whilst the 1st tier supplier alsohad the information from the 2nd tier supplier that they could share if they felt this wasappropriate. For example the 1st tier suppliers usually amended their product informationto remove price information before sharing this with participants at other company sites.

No directions were given regards seating positions or who operated the computer. Allteams were allowed 40 min to complete the task. In both conditions, the groups had tech-nicians on hand to help with technical problems and any task related difficulties.

Group performance was assessed informally by one of the researchers against criteriafor an effective solution to the problem provided by an experienced automotive engineer.The solutions were assessed in relation to the degree to which they completed the task, i.e.discussed and decided upon a short-term and long-term solution. The performance wasjudged against the domain expert’s criteria in a fairly straight forward way – i.e. was a rea-sonable solution suggested. This kind of real world problem does not lend itself to a morenuanced measure of performance. No noticeable differences in task performance wereobserved between the shared control and individual control conditions. From the obser-vations of the research team, and the analysis of the video tapes of meetings, it was clearthat the participants took the task seriously, and this was reflected in the discussions of theproblem and the solutions arrived at. Given the tight time constraints, groups performedwell overall and in a similar manner across conditions. In any case, as we know the impactof technology is more often observed in the communication process rather than on taskoutcome (e.g. Anderson, 2006; Anderson et al., 1997; Chapanis, 1988; Sellen, 1995).

The following extract from the discussions clearly illustrate the high degree of taskengagement that was shown by the participants. In addition, the realism with which supplychain status was role played is evident.

2.5. Discussion extract

Abbreviations used:OEM original equipment manufacture


SUPP 1st tier SupplierSP1 Speaker 1SP2 Speaker 2

2.6. Session 6 shared facility: negotiating cost

OEM-SP1: all right in the short-term we are going with the seals and the oil in the long-term we are actually going to relocate the exhaust or we will sort something out nowhow much is it going to cost us to go with the new seals and the oil?SUPP-SP2: well the choice of oil if you have a look at the whiteboard it’s the secondcolumn it’s DONATXOEM-SP1: you are not proposing to do it for free?SUPP-SP2: erm noOEM-SP2: sorry can we reach some sort of agreement on the priceSUPP-SP2: we can meet an agreement we don’t tend to do things for freeOEM-SP2: no we’re not asking for you to do things for free we just want to negotiateon a priceOEM-SP1: that’s just my kidding aroundOEM-SP2: we have commitments to meet and I’m sure you have as wellSUPP-SP2: yeah well OK the oil is a cheaper price than what you are using at presentlyand if we go back to the seals on the page. . .

3. Results

3.1. Communication analysis

To explore the impact of technology configuration and organizational status oncommunication in virtual team meetings, three different types of communicationanalyses were carried out. We investigated the amount of interaction among teammembers, the content of the discussions and the patterns of interaction among teammembers.

One of the sessions from the shared control condition was omitted from the analysisdue to inconsistencies in the experimental procedure (leaving eight sessions in the sharedcontrol condition). Full transcriptions were made of the discussions on a turn-by-turnbasis. For the purposes of this work, we defined a turn in a discussion as the time fromwhen one person began speaking until they paused and listened to someone else. Althoughusually one person speaks at a time, turns can overlap temporally. These raw transcrip-tions were used for calculating discussion lengths.

In addition, the contents of the discussions were analysed. Each turn was coded for thetype of talk it contained. The set of content codes were mutually exclusive and exhaustive.The following categories were used: turns which were concerned with attracting the atten-tion of other team members (Attention); turns which were concerned with which kind ofinformation was needed or had to be accessed to accomplish the task (Information); talkwhich was concerned with social relations such as greetings or light-hearted remarks(Social); talk which referred to or discussed the technology (Technology); talk which


was concerned with solving the task (Task) and talk which could not be classified (Unclas-sifiable). Examples of the coding of turns of talk are shown below.

Attention: ‘‘Jim are you ready to start ?’’Information: ‘‘We need to get the data up so we can see what’s gone wrong’’Social: ‘‘Who’s getting the tea?’’Task: ‘‘the max. temperature is well above that’’Technology: ‘‘click here to open it’’

All discussions were coded by one coder based on written instructions, which are avail-able upon request. To test the reliability of the scheme, two randomly selected discussions(approximately a 15% sample) were independently coded by a second coder and an anal-ysis of intercoder agreement was calculated using the Kappa statistic. The coding wasfound to be reliable (K = 0.76, k = 2, N = 334). Finally, each turn in the discussionswas coded for where it was directed: that is, whether it was addressed to someone acrossthe video link (‘‘cross site’’) versus whether it was addressed to someone present at thesame location as the speaker (‘‘local site’’). This coding was uncontroversial. It is usedto show differences in behaviour across the link and within a room for discussions inthe shared condition.

3.2. Participant coding

To determine who had controlled the technology interface in the shared facility teams,we administered a post-task questionnaire that asked participants whether they operatedthe computer at any time during the discussion. This information was checked againstvideo recordings of the sessions. Participants were classified as being Technology Control-lers or Non-Controllers. Most non-controllers never operated the computer at all,although a few controlled the interface for a very brief period during the discussion.The technology being controlled included the communication link, drawing on the whiteboard, accessing web based information resources. All participants could speak to otherteam members at either site and be heard.

Our results rely on a relatively small number of virtual teams and, in the individual con-trol condition, a relatively small number of participants. Accordingly, when reportingteam level comparisons, we use non-parametric statistical tests, which are clearly suitable,if conservative, in this context. When reporting participant level comparisons, we use non-parametric tests when the data are restricted to the individual control condition, but para-metric tests for the shared control condition because the sample size is reasonably large.Where non-parametric tests are employed, if parametric results are different we give themalso.

3.3. Technology configuration: shared facilities versus individual control

3.3.1. Amount of interaction

The number of turns in each discussion was totaled. Discussion lengths in the sharedand individual facility conditions were compared with respect to the total number ofturns/discussion. A Mann–Whitney U-test showed a significant difference in the numberof turns of talk in the two configurations (U = 1, p < 0.01). The shared facility discussions


were significantly longer than those in the individual control configuration. The medianturns of talk per discussion were:

Shared Facility – 315.0; Individual Control – 194.33.

Overall, discussions in the individual control condition contained 62% fewer turns com-pared to the shared control condition. These data appear to provide support for H1 andH1A.

Since turns can vary considerably in length, an alternative measure of discussion lengthis the number of words in each discussion. An analysis was also carried out on the numberof words spoken, which showed a similar numerical pattern: Shared Facility – 4105.0,Individual Control – 2528.5. A non-parametric Mann–Whitney U-test did not show thisdifference to be statistically significant (U = 11, p < 0.09) (though an equivalent parametrict-test did show a significant difference at p < 0.05).

To explore these data in more detail, an analysis of discussion length was conductedcomparing the amount of talk exchanged across the virtual team i.e. via the communica-tions technologies between different sites. As all the conversation in the individual controlcondition was conducted over the communications links, shared and individual controldiscussions were then compared using total cross-site talk from the shared facility discus-sions (excluding same-site talk). The two computer configurations produced very similaramounts of cross-site talk, with median numbers of turns of talk as follows: Shared Facil-ity – 188, Individual Control – 194.3. These did not differ significantly. (U = 23, p = 0.89,t-test also not significant).

When the number of words exchanged over the communication link was analysed thisagain showed no significant differences between the conditions:

Shared Facility – 2666.5, Individual Control – 2528.5.

Thus although hypotheses 1 and 1A receive partial support, in that communication dif-fers in the two technology conditions, the explanation is in two parts. Discussions in vir-tual teams where team members share technology were longer overall than those in teamswhere each team member had his own computer facility. The extra discussion in the sharedfacility condition was limited to exchanges at the home site. There was no difference in theamount of discussion across the virtual teams’ two locations.

The larger teams with shared facilities produced no more discussion with their remotecollaborators. This is not just a failure to reach a statistically significant increase in theshared facility conditions. Fewer turns of talk were exchanged in the larger shared facilityteams and virtually identical number of words were spoken. It is not that there is no obser-vable impact of increasing the size of a virtual team, or that the study is too small to revealthe impact. Additional team members significantly increase the amount of talk, but only ata single site. The predicted advantage of being able to draw in additional team members andso enlarge the pool of available expertise does not translate to better communication acrossthe distributed team if these individuals have to share the communications technology.

In this study we attempted to simulate our workplace observations where teams thatshared technology often did so because they had more members. We wished to investigatethe impact of the larger teams on the communication process. We also wished to see howthe size of the team related to the impact of the technology configuration. So a length anal-ysis was conducted controlling for the number of individuals contributing to each discus-sion in the shared facility condition (the individual control condition had only one personat each site). In order to calculate this, the total number of turns for any one discussion in


the shared condition was divided by the total number of contributors (which rangedbetween 4 and 7). The median number of turns of talk per team member was as follows:Shared Facility – 56.2, Individual Control – 64.7. The resulting median number of turns/individual was then compared to individual control using a Mann–Whitney U-test. No sig-nificant difference was found (U = 15, p = 0.24), a parametric t-test also showed no signif-icant differences between the conditions on this measure.

We would anticipate that larger teams would produce more discussion as the extramembers of the team would have information and suggestions to contribute to the discus-sion of the problem. Although the analyses support this view, we find that the addition ofextra team members in the shared facility condition results in more talk at a single com-pany site. Each member tends to contribute proportionally to the within company inter-action. The unexpected aspect of the data is that the presence of extra team memberswith experience and individual views does not lead to any more information beingexchanged via the technology across the virtual cross-company team.

3.3.2. Content of discussions

We also analysed the hypotheses about communication in terms of the content of thediscussions. A series of analyses were conducted comparing dialogues in the two computerconfigurations for each category of talk using Mann–Whitney U-tests. These revealed nosignificant differences between the computer configurations for any of the categories oftalk. A Kruskal–Wallis non-parametric analysis of variance was conducted across the dif-ferent categories of talk, collapsed across the two computer configurations (H(95) = 50.98,p < 0.05). As can be seen from these data in Table 1, task talk was the dominant categorywithin the virtual team discussions.

3.4. Control of the technology and corporate status effects

3.4.1. Amount of interaction

We had hypothesized that as well as computer configuration, two other factors wouldimpact upon communication in virtual team meetings. In teams where participants sharecomputer facilities, we predicted that individuals who controlled the interfaces would con-tribute most to the cross-site communication. We also predicted that team members fromcompanies lower in the supply chain would contribute less to virtual meetings.

To test these hypotheses, two separate analyses were conducted, one for each computerconfiguration. For the shared computer facility condition, all discussions were subjected toan Analysis of Variance with Supply Chain Status (2 levels: OEM and 1st Tier Supplier)and Role (2 levels: Technology controller and Non-controller) as between subject variables

Table 1Mean number of contributions per category per discussion

Shared facility Individual control

Attention 6.2 11.0Information 51.7 32.6Social 23.3 5.6Task 173.2 119.6Technology 38.8 18.0Unclassifiable 39.7 7.3


and Direction of Talk (2 levels: Cross-site and Same site talk) as within subject variables.This showed no significant main effect of supply chain status (F < 1), as participants fromOEMs and Suppliers contributed almost identical amounts of talk to the meetings onaverage.

Significant main effects of Direction of Talk and Role were found F(1,44) = 8.309,p < 0.05 and F(1,44) = 13.611, p < 0.05, respectively, as well as a significant interactionbetween the two (F1,44 = 18.94, p < 0.01). Analysis of this interaction was conducted usingsimple main effects for the effect of computer operation at each level of direction. Thisrevealed that the effect of role only held for cross-site talk. As can be seen from Table 2,all participants contributed equally to same-site talk, but technology controllers dominatedthe cross site discussions. These data provide clear support for H2 but not for H3.

Equivalent analyses were also conducted to explore the effects of supply chain status forthe meetings in the individual facility condition. As this again reduces the sample size con-siderably, it was considered that non-parametric statistics were more appropriate, and thusKruskall–Wallis One Way Analyses of Variance were conducted to test the overall amountof talk in terms of number of turns of speech contributed by team members from each typeof company.

An analysis of the differences in the total number of turns/discussion between compa-nies in the individual control configuration was conducted. This revealed a significance dif-ference between the companies, H(2) = 11.58, p < 0.05. Multiple comparisons revealedthat participants from 2nd tier Suppliers contributed less than either those from theOEM or the 1st Tier Supplier, who did not differ significantly. These data which are shownin Table 3, provide partial support for H3.

3.4.2. Content of discussions

To pursue the influence of task role, i.e. being a technology controller or not, a furtheranalysis was conducted to test whether the content of technology controllers’ conversationdiffered from non-technology controllers. A mixed Analysis of Variance was conductedwith Status (2 levels: OEM vs. supplier) and Role (2 levels: Technology controller vs.Non-technology controller) as the between subjects variables and Direction (2 levels:cross-site vs. same-site) and Type of Talk (6 levels: attention vs. information vs. social

Table 2Mean number of turns per discussion by direction and role in shared facility condition

Same site Cross site

Technology controllers 23.27 51.14Non-controllers 22.44 16.78

Table 3Median number of turns per discussion by supply chain status in the individual control condition

Median number of turns

1st tier 91OEM 682nd tier 35

Table 4Mean number of turns/dialogue by role, direction and utterance function for two site configuration

Direction Utterrance function

Role Atten. Info. Social Task Tech Unclass.

Cross-site Technology controller 1.54 10.14 4.78 27.54 5.32 1.82Non-technology controller 0.59 2.41 1.83 9.31 1.29 1.35

Same-site Technology controller 0.00 2.91 0.64 11.46 4.23 4.00Non-technology controller 0.00 2.52 0.76 10.86 2.58 5.14


vs. task vs. technology vs. unclassifiable) as the within subjects variables. Of interest wereinteractions between role, direction and type of talk. Along with the main effects of direc-tion and role found in the previous analysis, a main of effect of Type of Talk was found,but this needs to be qualified in the light of the significant three-way interaction betweentype of talk, direction and role F(5,44) = 8.928, p < 0.01. As can be seen from Table 4, twotypes of talk contribute very largely to this interaction, with a fourfold increase in theamount of Information talk and a three fold increase in Task talk from technology con-trollers in their cross-site contributions. So the kinds of talk associated with obtaining thenecessary information and solving the task are strikingly high in these contributionsbetween the two locations, but only from the virtual team members who control the tech-nology. These data are illustrated in Table 4.

Equivalent analyses were also conducted to explore the effects of supply chain status forthe meetings in the individual facility condition. As this again reduces the sample size con-siderably, it was considered that non-parametric statistics were more appropriate, and thusKruskall–Wallis One Way Analyses of Variance were conducted to test the overall amountof talk in terms of number of turns of speech contributed by team members from each typeof company.

A further series of analyses were conducted to investigate if supply chain statusimpacted on the types of talk contributed by team members. As there were significant dif-ferences in the total amount of talk, the amount of each type of talk was proportionalizedto take into account the total number of turns per dialogue. Kruskall–Wallis analyses wererun on each type of talk separately with Supply Chain Status (3 levels: OEM vs. 1st tierSupplier vs. 2nd tier Supplier) as the between subjects variable. These analyses revealedonly one significant difference: team members from 2nd Tier suppliers contributed a smal-ler proportion of task focused talk than team members from higher status companies(H(2) = 6.431, p < 0.05).

These analyses show modest influences of supply chain status on communication invirtual team meetings. Participants role-playing team members from lower tier supplierscontributed somewhat less to the meetings than did those from higher status companies,and the type of talk which shows this reticence most clearly, was task focused talk. In oursimulation study these participants each had their own communications facility, but tomirror what we had learned concerning the situation in the workplace, this was a lesstechnically sophisticated facility than those available to participants from higher statuscompanies. This difference if anything should exaggerate any status effects but the impactof organizational status even when accompanied by typical technological restrictions wasmodest.

Table 5Mean number of turns/discussion of cross-site talk by computer configuration, supply chain status and role

Non-controller Technology controller

Shared facility OEM 18.67 56.75Shared facility 1st Tier Supp. 15.37 52.37Individual facility 2nd Tier Supp. 33.84


An alternative arrangement of course would have been to bring the team members fromthe lower tier suppliers to the sites of the higher status companies and have them contrib-ute from these sites, sharing the facilities there. Time constraints on our study meant wewere unable to simulate and test this arrangement, so we decided to examine the contribu-tions of participants from each type of company in each configuration. As our analyseshad shown that being a technology controller was a salient factor in influencing patternsof contributions this feature was also included. These data are shown in Table 5.

Although the design does not permit statistical analyses of these data, it is worth notingthat even with their more limited technical facilities, participants from 2nd tier suppliers,contributed on average far more often to cross-site discussion than team members who didnot operate the interface at either the 1st tier suppliers or the OEM. Having their owncommunications facility, even if technically restricted, seems to offer a considerable benefitto lower status participants in virtual teams in terms of their ability to contribute fully tovirtual team interactions. It seems likely if they were sharing facilities, for example with a1st tier supplier whilst communicating with a remote OEM, that these participants wouldcontribute rather less to the cross-site discussions.

3.4.3. Patterns of interaction

The analyses so far have shown that the task role which team members adopt, ofbecoming the technology controller or not, influences the amount they will contributeto virtual team meetings, at least in terms of communication with remote participants.To investigate this issue further we decided to explore how the participants’ task roleimpacted upon patterns of interaction. To do this we utilized the concept of the initiationof conversational floors (Parker, 1988). Several previous researchers such as Parker (1988),Carletta et al. (1998), and Ishizaki and Kato (1998) have shown that much of the interac-tion between participants in group discussions, is in fact a series of two party conversa-tions. Parker (1988) described a unit of conversation called a ‘conversational floor’which captured this observation, being a sequence of speakers’ turns, at least three turnslong, involving only two participants in a larger group.

We decided to investigate whether the number of such conversational floors, whichteam members initiated with remote participants was influenced by their adopted task roleas technology controller or non-technology controller.

The total number of cross-site floors initiated between pairs of participants werecounted. A floor was defined as sequences of ABA or longer (ABA being where A speaks,B replies, and then A replies). The mean percentage of cross site floors initiated betweenpairs of participants in relation to role was calculated, controlling for the number of par-ticipants in each category. The overall percentage of floors initiated in cross-site talk bytechnology operators was 80% whilst only 20% of floors were initiated by non-technologyoperators. These data are shown in Table 6.

Table 6Cross site floors initiated by technology controllers and non-technology controllers in the shared facilityconfiguration

Dialogue pair Cross site floors initiated

tc-tca 122 (54%)tc-ntcb 59 (26%)ntc-tc 33 (14%)ntc-ntc 14 (6%)

a Technology controller initiates floor with technology controller.b Technology controller initiates floor with non-technology controller.


4. Discussion

We wished to explore the nature of communication during virtual team meetings. In theworkplace we had observed and analysed of a small number of virtual team meetings,where employees in different companies used multimedia IT tools to support their collab-orative working. We had hypothesized that the ways these facilities were implemented andthe relative status of the organizations, impacted on the communication process (Carlettaet al., 2000). Here we wished to explore these factors in a lager sample of virtual teammeetings in a more controlled setting that still captured key features of the workplace.

To do this we devised what we termed a simulation study where we recruited partici-pants with considerable industrial experience, similar in many cases to that of the teamswe had observed in the workplace. These participants enthusiastically role-played the teammembers from different companies engaged in solving an engineering design problem. Thetask scenario that we had devised was also based on a real world problem. This method-ological approach involves a number of advantages but also compromises. It allowed us toexplore systematically the impacts on communication of different computer configura-tions, participants’ task role and the status of their employer in the supply chain, in 15comparable virtual team meetings involving 70 participants.

We think this approach is potentially valuable because the great majority of theresearch literature on team and virtual team working is based on ad hoc teams of studentsin the laboratory tackling fairly unrealistic tasks. Such approaches have value and indeedwe have used this approach in many of our own previous studies (see for example Ander-son et al., 1997). There are cases where such research methods are less appropriate such asthe study of the impact of technology on group interaction, status and engagement.

Communication among virtual team members was influenced by the way the technol-ogies were implemented. Where team members shared a single communications facility,the person who operated the key board, became dominant in cross site communicationdespite the fact that communication was verbal and the audio facility (full duplex audio)made contributions from any team member perfectly audible at either site. This individualseemed to fall into the role of company spokesman. The team members who did not act astechnology controllers largely restricted their contributions to discussions with their co-present team mates. They did not tend to engage in discussions with their collaboratorsat the remote site. The potential advantages of having a larger virtual tam with a rangeof expertise to contribute and share, was considerably diluted by this effect.

One plausible explanation of this phenomenon would be that certain individuals arenaturally dominant and tend to take leading roles in all discussions. This was not the case


however in this study. The technology controllers only led discussions across the commu-nication link to the other site. They did not contribute more than others to discussions attheir own location. Rather the fact that a small group of individuals were gathered at asingle site sharing a communications facility seemed to elicit this approach to cross siteinteraction. This phenomena may appear related to ‘social loafing’, that is the tendencyfor members of a larger group to expend less effort than when they work as individuals(Latane, Williams, & Harkins, 1979). This cannot be the sole explanation, as the amountof interaction at a single site increased with the presence of extra team members. Driskellet al. (2003) suggest that virtual team working might be a context that encourages socialloafing, and recommend more research on the topic. Our study would suggest the relation-ship is rather more complex and is influenced by the way the virtual team technologies areused.

The outcome of this behaviour was that the added value of having additional team mem-bers was reduced, as no more communication or exchange of ideas occurred despite havinga larger team with their additional expertise. Stasser and his colleagues have shown in aseries of studies (see for example Stasser & Vaughan, 2000) how difficult it is even inface-to-face meetings to ensure good sharing of information among the group, particularlyof unique information known to only single individuals. In our study we have evidence thatin distributed groups, the way the technology to support collaboration is implemented, mayexacerbate this. The central role of technology controllers and the relative marginalizationof non-technology controllers was illustrated in both the total amount of cross sitecontributions and in the way extended conversational floors were elicited. Technology con-trollers initiated the majority of their conversational floors with other technology control-lers at the other site and few with non-technology controllers. Non-technology controllerson the other hand initiated most of their floors with the technology controllers and few withother non-technology controllers across the link. The majority of sub-conversations, whichtake pace between remote sites, were initiated by computer-operators with other technol-ogy controllers. The extent of such cross-site conversations between non-technology con-trollers was very modest (6% of floors). Thus there were few opportunities for ideaexchange by most team members across the communication link, not because of technologylimitations but because of the way individuals tend to respond to a shared communicationsfacility.

The advantages of being able to recruit additional team members did not fully materi-alize, as these individual only added to discussion at their own location. We might spec-ulate about why the larger teams with shared facilities had more discussion. This mightbe because the larger group naturally leads to more talk. Alternatively, sharing communi-cation facilities might in itself tend to lead to more talk. Further studies would be requiredto tease out these alternative explanations. The important finding of the present study isthat whatever causes the increased interaction at a single site did not lead to more commu-nication between sites. If we want to encourage free and open communication betweensites, surely the very essence of effective virtual team working, then sharing facilities seemsto hamper this.

We found no more information was exchanged across the virtual team as a result of thepresence of extra team members. This was true for both OEMs and 1st tier suppliers.Overall in fact we found communication patterns tended to be similar across differentorganizations with only modest effects of organizational status. One significant impactof status did emerge. Participants from 2nd Tier suppliers said less than those from higher


status companies. The general advantage of providing team members with individualcomputing and communication facilities however was again clear. These team memberscontributed more to discussions with other sites than higher status team members whodid not run the interface in the shared facilities teams. This occurred despite the fact thatthe individual kit provided to these lower status organizations reflected their status (andtheir likely facilities in the real work place). So their equipment was less sophisticated thanthat of other team members, having only half duplex audio requiring the individual toclick an icon before speaking rather than having a continuously open communicationchannel. This audio configuration has however been shown to offer advantages when com-munication facilities are restricted (Sanford et al., 2004). It encourages participants toadapt their communication to the context of collaborating remotely (for example by tak-ing care to avoid interruptions, and producing longer more complete turns of talk) ratherthan encouraging them to assume they can interact as casually as in a face-to-faceconversation.

These observations result from very precise and detailed analysis of the transcribed andcoded discussions. Such careful micro-level analysis is needed we believe to illuminate thesubtleties of group behaviour. Simpler methods such as questionnaires are often not sen-sitive enough to reveal these kinds of phenomena, which are not always available to theparticipants’ conscious assessment of the situation.

Over time the patterns of communication we observed seem likely to impact on teammembers feeling of engagement in the virtual team Researchers such as Bos, Olson, Ger-gle, Olson, and Wright (2002), Bradner and Mark (2001, 2002) and Potter and Balthard(2002) have reported that distributed teams supported by technologies often have difficultybuilding trust and commitment. The communication patterns of teams where membershave to share facilities would seem likely to add to these general team working difficulties.

Storck and Sproull (1995) in a longitudinal study of distance learning, report similarnegative impacts on students’ perceptions of distant classmates. They suggest guidanceon how to manage the communication process in remote interactions. Our findings suggestthat this guidance should include advice about the likely communicative consequences ofsharing facilities.

The communication analyses illustrate the ‘keyboard squeeze’ effect suggested by ourworkplace observations. Non-technology controllers in shared facility virtual team meet-ings are relatively marginalized and are less likely to exchange ideas and information withteam members present at the other site. The analysis of the content of the interactions sug-gests that it is the most task relevant types of talk that are likely to be carrying these effects.Encouraging greater interaction across the communication link is likely to encourage moresharing of problem-solving talk. The team members who are not in control of the interfaceare very unlikely to be bouncing their ideas off their equivalent virtual team members atthe remote site.

The implications of this study seem clear. If an organization wishes to use virtual teamworking and also wishes to encourage open communication and active interaction acrossthe distributed team, the way supporting technologies are implemented needs careful con-sideration. Sharing facilities however technologically sophisticated may have unforeseenand undesirable consequences. The results of this systematic lab study confirm many ofthe observations we made in field studies and strength the suggestions for work-place prac-tices offered in Carletta et al. (2000). Key considerations include explicit preparation andtraining for virtual teams as a way of working and collaborating. This should include but


go beyond technology training. One way to encourage effective communication practicesin virtual team meetings might be through the use of facilitators to encourage open andinclusive patterns of communication across the distributed locations. This is importantnot just from the results of our study but also from the results of a number of studiesof work place virtual team working which have also reported difficulties in eliciting effec-tive team behaviours and feelings of reciprocity among the distributed workforce (e.g.Herbsleb, Mockus, Finholt, & Grinter, 2000; Olson & Olson, 2000).

Researchers on the psychology of dialogue such as Clark and his colleagues, highlightthe benefits of direct interactions between speakers as these lead to mutual understanding(see for example, Clark & Wilkes-Gibbs, 1986; Schober & Clark, 1989). The implicationsof this approach to dialogue would seem to suggest that direct interactions among mem-bers of a larger group would also facilitate increased mutual understanding of the issuesunder discussion. There are a few researchers who have suggested that there may be someefficiency gains to be had from less equitable patterns of communication, notable whengroups are operating under time pressure or where expertise is unequally distributedacross the group (see for example, Farris, 1973; Vroom & Yetton, 1973). In most settingshowever there would seem to be advantages to be had from encouraging open commu-nication from all team members, particularly given the challenges of effective distributedworking. The way the technology is implemented seems to make this outcome more orless likely.

Our final point is methodological. In exploring the impact of computers on humanbehaviour researchers are faced with a methodological dilemma. Experimental studieswith many replications of identical conditions in the laboratory provide advantages. Asresearchers we can test predefined experimental hypotheses with large samples of compa-rable participants. Many studies in Human Computer Interaction have used such meth-ods, drawing on the scientific techniques commonly used in the psychology laboratory.The disadvantages of such a research approach is that the problems that can be studiedare often unrealistic. There are then questions about the generalizability of the findingsof such lab studies. Will the behaviours that were observed on simple decontextualizedtasks occur outside the lab, for example in the workplace?

One alternative approach to this problem has been developed in other disciplinesnotably by researchers in the ethnographic tradition. They have approached the studyof the impact of technology for example through prolonged observations in the field.Several researchers have used this approach to describe the complexities of the use oftechnology in the workplace, e.g. Suchman (1987) and Heath and Luff (1992). Research-ers from other traditions have also grappled with these issues. For example Olson et al.(1995) in their studies of the effectiveness of video mediated collaboration, used a con-trolled experiment with a realistic problem and existing groups with commercial experi-ence. In the study reported in this paper we have attempted to find our owncompromise to the questions of validity, generalizability and control. We began byobservations of behaviour in the field and then tried to identify key features for system-atic exploration in a semi-controlled laboratory simulation study with a real problemand participants of similar experience to those observed in the workplace. This processinvolves some trade-offs and disadvantages but we hope will be considered as anotheruseful approach to the difficult question of arriving at an appropriate scientific method-ology for investigating new forms of computer supported collaborative working such asvirtual teaming.


Acknowledgements

The authors are very grateful to the members of the EC ACTS project AC070 TEAMproject at the University of Warwick, for their assistance and use of the TEAM technologyfor this study.

The research described here was supported by a Grant (L125251033) from the UK Eco-nomic and Social Research Council under their Innovations Programme to C. Dent andA. Anderson.

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