Proceedings of the 38th Hawaii International Conference on System Sciences - 2005 The Effect of Task Design, Team Characteristics, Organizational Context and Team Processes on the Performance and Attitudes of Virtual Team Members D. Sandy Staples and Ann Frances Cameron Queen’s School of Business, Queen’s University sstaples@business.queensu.ca, acameron@business.queensu.ca Based on Cohen’s [4] model of traditional teams, the effectiveness of members of six virtual teams were investigated. Case studies in three different industries were conducted. Thirty-nine team members, along with the teams’ manager/sponsor, were interviewed. Previously published analysis of this data [18]investigated patterns between various team input factors and the resultant virtual team member attitudes (i.e., satisfaction and motivation). In this study, the relationship between input factors and a team member’s perception of team performance was examined. Positive patterns were found between team performance and interpersonal skills, team size, team turnover, team potency, team spirit, and innovations. In order to fully understand virtual team effectiveness, the results of both this performance study and the previous attitudes study are discussed. Taken as a whole, this research program has important implications for organizations with virtual teams and the researchers who study this new work. outcomes such as quality, productivity and controlling costs. Previous analysis of the case studies [18] reported in this paper focused on the former category of outcome variables and examined the effect of various input factors on virtual team member attitudes. The purpose of this study is to examine the factors and processes that affect the latter category, virtual team performance, and to discuss the impact of both the performance and attitudes research on our understanding of virtual team effectiveness. This paper is organized as follows. The research framework used to guide the case studies and the previous attitudinal findings are presented in section 2. Section 3 discusses the methodology used in the case studies and describes the characteristics of the teams studied. In section 4, the results of the analysis are presented. Finally, section 5 discusses the results of both this performance study and the previous attitudes study and how they contribute to an overall understanding of virtual team effectiveness. Implications for both practitioners and researchers and suggestions for future research are also presented. 1. Introduction 2. Research Framework Groups and teams in organizations have been formally studied for over half a century, resulting in thousands of studies and a huge body of literature [11]. Virtual teams, or teams with geographically-distributed members, have been growing in popularity over the last decade or so, but have not yet been extensively studied and how to work effectively in virtual teams is not yet fully understood [14]. Typical team effectiveness models (e.g., [4, 11, 14, 19] – see Figure 1) are based on collocated teams, and usually assess two main categories of effectiveness outcome variables: (1) attitudinal outcomes such as satisfaction with the job, satisfaction with the team, motivation, and organizational commitment, and (2) performance A self-managed team effectiveness model developed by Cohen [4] was used to guide the case studies. Cohen developed her model based on an extensive review of the relevant research literature and an examination of other team effectiveness models. As can be seen in Figure 1, Cohen’s model consists of four categories of input variables that potentially impact team effectiveness. These inputs are proposed to impact the three output categories of team effectiveness: team performance, attitudes and behaviors (and the outputs are interrelated). Since Cohen’s model pertains to traditional selfmanaged teams, modifications were made to the model to make it fit a virtual work setting. First, it is Abstract 0-7695-2268-8/05/$20.00 (C) 2005 IEEE 1 Proceedings of the 38th Hawaii International Conference on System Sciences - 2005 important for team members in a virtual setting to have information technology skills. In addition, team members need to be given appropriate tools and opportunities to use technology skills to accomplish their work. As such, the variable Information System (IS) Skills was added to the Group Composition list of variables, and IS Resources was added to Organizational Context. Figure 1. Virtual Team Effectiveness Model (adapted from [4]) Inputs Team Task Design - variety of skill, identifiable objective, significance, autonomy, feedback, interdependence Team Characteristics - a: Composition technical skills, interpersonal skills, size, stability, IS skills, degree of virtualness/isolation - b: Team Beliefs norms, group efficacy - c: Team Process coordination & caring (team spirit), sharing of expertise, implementation of innovations Organizational Context that supports Employee Involvement - power, information, rewards, training, resources, IS resources Encouraging Supervisory Behaviours - self-observation, evaluation, goalsetting, criticism, expectation OutputsEffectiveness Team Performance Outcomes quality, productivity, controlling costs Attitudinal Outcomes - with Quality of Work Life - satisfaction with job, team, social relationships, growth opportunities, motivation - trust in management & team - organizational commitment Withdrawal Behaviours Outcomes absenteeism, turnover Second, the degree of virtualness could also potentially affect performance of geographically disperse team members. Degree of virtualness measures how often the team works from different locations and can vary from never meeting face-to-face to occasionally working virtually. Team members working in a highly virtual team may experience higher degrees of isolation from other team members as well as other members of organization. Thus, Degree of Virtualness was added as a Group Composition variable. Third, the scope of this study will be limited to a sub-set of Cohen’s model. While the original model includes three categories of outputs, the focus of this analysis is on performance outcomes and discussion of these outcomes along with attitudinal outcomes. In particular, the paper will examine factors and processes that enhance a team member’s perceptions of team performance. On the input side, supervisory behaviours were not included in this study due to practical limitations and the fact that Cohen, Ledford and Spreitzer’s [6] test of Cohen’s [4] model did not find any significant relationship between supervisory behaviour variables and effectiveness measures. The three groups of input variables that were included in the study are explained below. 2.1. Task Design Both Hackman and Oldham’s job characteristics theory and sociotechnical theory suggest that group task design is critical for employee motivation, satisfaction and performance [4, 11]. Both theories suggest that to positively impact performance and attitudes, the task should be designed so that a variety of skills are required, it should be a whole and identifiable piece of work so that members can see the outcome of their efforts, the task should be perceived to have significant impact on the lives of other people, the team should have considerable autonomy and independence in determining how the work will be done, and regular and accurate feedback should be provided such that the team can understand how it is performing. Previous analysis of this study’s data with regard to attitudes did find a relationship between motivation and task design characteristics such that virtual team members with low motivation tended to have lower beliefs in the significance of the task and believed that their team had low autonomy [18]. Task design characteristics were also related to satisfaction with the team in that individuals with lower satisfaction were more likely to believe that the team had lower autonomy and that responsibility for the task was not shared equally. 2.2. Group Characteristics: Composition The collective knowledge and skills of a team will impact the team’s ability to carry out its task [14]. This includes both technical skills, information systems (IS) skills and interpersonal skills. IS skills are needed to use the information technology tools and systems that are available to communicate and share information. The size of the team can also affect the collective ability of the team to do its task [10]. If the team size is too big, higher coordination costs result. If it is too small, it will not have the resources needed to complete its work, and team members will be less likely to be committed to the team. Stability of team membership is also an important factor. If turnover is high, time and effort will be spent orientating new members, performance norms will not develop, and performance will suffer. However, some turnover can be beneficial, in that it could revitalize a stagnant team and enhance creativity. There has been limited empirical evidence to suggest that greater geographic distribution of a team leads to lower performance [7]. This is presumably due to the reduced face-to-face contact, reduced opportunities to build social relationships, and 0-7695-2268-8/05/$20.00 (C) 2005 IEEE 2 Proceedings of the 38th Hawaii International Conference on System Sciences - 2005 the difficulties of communicating and coordinating virtually. This implies that higher virtuality could be negatively related to team performance. The earlier analysis of these case studies demonstrated the importance of group composition to virtual team effectiveness [18]. Individuals who felt that interpersonal skills were lower among the other team members did not tend to be as motivated to do the task. As well, team members with lower satisfaction with their team tended to assess their team’s interpersonal skills lower and often felt that the team lacked some technical skills. 2.3. Group Characteristics: Group Beliefs Group beliefs about the team’s performance have been found to be a strong predictor of group effectiveness in previous research [16]. In this study, group beliefs were assessed via a concept called group potency. Group potency captures efficacy beliefs at the group level. Group potency (sometimes referred to as group efficacy) is “a collective belief in the capability of the group to meet a task objective” [9, p. 71]. Group potency was found to be linked to motivation and satisfaction, the attitudinal component of virtual team effectiveness, in the previous analysis [18]. Team members who had low motivation generally had lower beliefs about their team’s abilities. Members who felt their team had high capabilities (i.e., a high group potency rating) had high satisfaction with their team. 2.4. Group Characteristics: Group Process Three groups of variables pertaining to group process were examined: coordination and caring (i.e. team spirit), sharing of expertise, and implementation of innovations. Good coordination among team members leads to working together without duplication and wasted efforts. Caring about each other implies working together with energy and team spirit. Sharing and benefiting from others’ knowledge and expertise is important to support effective cross-training and decision-making and to fulfill interdependencies. Implementation of innovations describes a team’s ability to create and adopt new ways of working to better complete their tasks. This ability is important so that a team can adjust to changing conditions and make improvements in its work processes. The three sets of process variables are derived directly from Hackman’s [13] model of group effectiveness, in which process is viewed as a consequence of input factors, a contributor to performance and is reciprocally influenced by performance. Again, the earlier attitudinal study found that group processes do impact virtual team effectiveness [18]. For example, a team member who had low motivation also perceived that the team’s spirit was low. Also, people who had lower satisfaction with their team felt that there was not a strong team spirit and often felt that coordination could be improved. 2.5. Organizational Context The organizational context in which a team works can create the conditions for a team to be successful or for it to fail [10]. The team with the best internal processes may still perform poorly if it lacks the resources or information needed to do its task. A team will not be able to make good decisions without proper information, sufficient training, and adequate resources. Therefore, a series of organizational context variables were examined. These variables potentially interact to create an environment where the employee wants to be involved and can participate to complete their tasks effectively. Specific variables examined were: (1) the reward system (it should be designed so it is tied to performance and development of capability and contributions to the team); (2) the availability of training (it should be available to enable employees to develop the skills and knowledge required to complete their tasks); (3) access to needed information (without this, employees will not be able to effectively complete their tasks); and (4) resources available, including information technology infrastructure to communicate and share information electronically in the virtual setting (adequate resources are needed to enable employees to complete their tasks). Interestingly, the earlier analysis did not reveal any distinct patterns between organizational context variables and virtual team member attitudes, possibly due to a lack of variance in most of the variables [18]. The Cohen [4] model was designed for traditional teams and the results reported above have largely been based on studies of non-virtual work. Examination of the relationships between input variables and effectiveness in a virtual team context is warranted and will be explored in this study using a case study methodology. The methodology used is described in the next section. 3. Methodology 0-7695-2268-8/05/$20.00 (C) 2005 IEEE 3 Proceedings of the 38th Hawaii International Conference on System Sciences - 2005 This section provides details on how the data were collected and analyzed, and it provides details of the teams that participated in this study. 3.1. Data Collection and Analysis 3.1.1. Case studies. Case studies of six virtual teams from three different companies, in different industries (i.e. high-tech, consulting, and manufacturing), were conducted. A total of 39 team members were interviewed, either face-to-face or via the telephone. In addition to the team members, the manager/business sponsors of each team were interviewed to learn their perspectives on the effectiveness of the teams. The semi-structured interviews typically lasted 1.5 hours each and a case-study protocol was followed to ensure consistency across the interviews. The specific questions that were asked to collect data about the output variables and input variables are provided in Appendix A. Most interviews were taped on audiotape (a few participants did not allow this). Transcripts were prepared from the interviews (resulting in over 1,000 pages of text) and entered into a qualitative analysis software package (N6 from QSR International). Each transcript was coded, as described below. 3.1.2. Coding the transcripts. A tree of nodes was initially built where the nodes represented the constructs of interest and the levels within the construct. The initial list of nodes was based on the model guiding the study and the questions used in the interview. Two coders then separately coded one complete interview with the initial list of nodes. The list of nodes was modified slightly by collapsing a few nodes and creating a few new ones to capture findings not initially anticipated. After this initial training and development period, both coders coded a random sample of ten percent of the transcripts to assess interrater reliability. Inter-rater reliability was done using the Bourdon [3] ICRV (Inter-Coder Reliability Verification) technique. Inter-rater reliability was 80%. This was deemed acceptable so the list of codes (i.e. the nodes) was finalized and the rest of the transcripts were coded by one person. 3.1.3. Analysis. Once the coding of the transcripts was complete, analysis was done to identify patterns of factors that potentially affected how virtual team members perceive team performance. Initially withincase analysis (i.e., at the specific team level) was done [15]; however, variance was limited within some of the teams so across-case analysis was then completed using the individual as the unit of analysis. Matrices were created for each of the outcome variables and for each of the blocks of input variables. These matrices were then examined to see if any patterns appeared to emerge for respondents who were high on the specific outcome variable (6 or greater) versus respondents who were low (less than 6) on the outcome variable. 3.2. Characteristics of the Teams in the Sample In order to provide context to the reader, short descriptions of each team are provided below. The nature of the task, the type of team, and the degree of virtuality present (i.e. how geographically-distributed the team was) are described. To ensure confidentiality and anonymity, the identities of the companies, the teams, and the team members are not provided. 3.2.1. Nature of the tasks and duration of the teams. Teams A and B were long-term project teams developing new product lines within their organization. Teams C and D were developing new product features for an existing product and had just about completed their tasks when the interviews took place. These teams had been together approximately 9 months so they can be thought of as medium-term project teams. Teams E and F were on-going teams that provided products to internal service groups, and most people had been on the teams for at least one year. Therefore, these were permanent teams. Teams A through D felt their tasks were quite complex and that there was a great deal of interdependence among the team members to get the task completed. Teams E and F felt their tasks were more routine and that usually they had relatively low dependence on other team members to complete their task. Complexity and interdependence did vary somewhat for teams E and F, depending on the specific task being completed. 3.2.2. Technology used. All teams used teleconferencing and e-mail heavily. Four teams used Lotus Notes a great deal to share information and coordinate activities. The other two teams used an internal intranet system to share documents and resources. NetMeeting was used occasionally and videoconferencing was rarely used. Two teams used instant messaging heavily. 3.2.3. Degree of virtuality. Teams A, B and D were spread across multiple cities in North America. Team C was similar, except there was also one member located in India. Teams E and F were more distributed with members in North America, Europe and Asia. Face-to-face contact varied considerably across the 0-7695-2268-8/05/$20.00 (C) 2005 IEEE 4 Proceedings of the 38th Hawaii International Conference on System Sciences - 2005 teams. Teams A and B met face-to-face a few times per year or more. Team C met face-to-face once during the duration of the project. Team D never met face-to-face. Teams E and F met face-to-face approximately once per year. 3.2.4. Reporting structure. Four teams were selfmanaged. They reported to directors or a panel of business sponsors. The management relationships were typically described as hands-off. The other two teams had a more direct reporting relationship to a manager and had more structure in place. Four teams felt the team was given a great deal of autonomy to carry out their task while the other two felt the autonomy was fairly limited, as their work was fairly structured and routine. 3.3. Construct Measurement Perceptions of team performance were measured as outlined in Appendix A (performance was defined in terms of effectiveness). Five sets of input variables were assessed: task design, team composition, group beliefs, team process, and organizational context. Five indications of the task design were collected from team members. We asked about the variety of skills needed for the task, the significance of the task, autonomy given to the team to carry out their work, the amount of feedback provided on the team’s performance, and if the responsibility for the task was shared equally among the team members. Six indications of team composition were collected from team members. Three types of skills (technical, IS and interpersonal skills), team size and stability, and degree of virtuality were examined. Group beliefs were assessed using the team potency scale. Individual average values varied from 6.0 to 9.6 (out of a possible range from 1 to 10, with 10 being high potency). Four indications of team process were used: team coordination, team spirit, sharing of expertise, and implementation of innovations. Six aspects of organizational context were examined. These were reward systems, training availability and support, access to needed information, access to needed resources, provision of information technology resources, and power/decision-making authority. 4. Results Found In this section, the findings for perceived team performance are presented first followed by the patterns found between the attitudinal variables and team performance. 4.1. Perceived Team Performance No clear patterns were found among the task design variables and team performance, although people who felt their team had lower performance tended to identify that feedback was not common. Three patterns were found among the team composition variables and team performance. Individuals with lower perceptions of their team’s performance were more likely to believe that the interpersonal skills of team members needed improvement, that the size of the team was too small, and that turnover within the team was significant. A strong positive pattern was found between team performance and group potency perceptions. Unpaired t-test analysis found people with high perceptions of team performance has statistically significantly higher potency beliefs (t = 3.07, p = 0.004). Two patterns were found between the process variables and perceived team performance. People who felt their team had good performance felt that there was a strong team spirit and were much more likely to identify innovations that had occurred to make the team more effective. No patterns were found between team performance and the organizational context variables. 4.2. Relationships between Attitudinal Outcomes and Performance Outcomes Analysis of the patterns between the attitude outcome variables and team performance perceptions found that people with low satisfaction with their team were more likely to rate their team’s performance as being low. People with high motivation were more likely to rate their team’s performance as being high. This is consistent with theoretical suggestions in the Cohen model specifying effects of attitudes on performance and vice versa. The next section will discuss the findings, present implications for organizations that have virtual teams, and make suggestions for future research. The overall findings are summarized in Table 1, where an “X” in the cell indicates that a pattern was found between the input variable and the output variable. Note, Table 1 only includes input variables that were found to have patterns with one or more output variable, for team performance and the analysis of attitudes. In all cases, the nature of the patterns was positive – e.g. negative/low perceptions of the input variable were found with low perceptions of the output variables. 0-7695-2268-8/05/$20.00 (C) 2005 IEEE 5 Proceedings of the 38th Hawaii International Conference on System Sciences - 2005 Table 1. A Summary of the Patterns Found Input Variables Significance of the Task Responsibility Shared Equally Autonomy Interpersonal Skills Technical Skills Team Size Output Variables Perceived Satisfaction Motivwith the ation1 Team 1 Team Performance X2 X X X X X X X X Turnover X Team Potency Coordination X X X X Team Spirit Innovations X X X X 1. Results from previous analysis of attitudinal outcomes. 2. An “X” indicates a pattern was found for that specific pairing of input and output variables 5. Discussion In order to fully understand virtual team effectiveness, both these performance results and the previous attitudes analysis are discussed. The findings suggest that, within the teams studied, good team performance is associated with having adequate interpersonal skills, low turnover within the team, adequate team size so resources are present to complete the tasks, positive beliefs about the abilities of the team, and strong team spirit, and creating innovative ways to coordinate the team and help carry out its tasks. Although our research design does not allow us to make any conclusions of causal direction, previous research (see Section 2 of this paper) would suggest that improving these input variables would lead to increased motivation to work on the team’s task. The findings on the attitudinal outcomes suggest that motivation is positively associated with perceptions of task significance, autonomy, interpersonal skills, beliefs about the team’s ability to do the task and team spirit. The findings also suggest that satisfaction with one’s team can also be enhanced by designing the task so responsibility is shared for it equally, providing higher autonomy to the team, developing stronger interpersonal skills, ensuring technical skills are adequate for the task, enhancing team potency, improving team spirit, and having good coordination with the team. The findings also suggest a positive relationship between motivation and team performance, implying that actions that enhance motivation will have an indirect positive impact on team performance. The discussion below deals with each of the input variables in the order listed in Table 1 and offers several implications of these variables for virtual teams and their organizations. Significance of the task appears to be positively linked to motivation. This implies that managers and leaders of virtual teams should work hard to make individuals aware of how important the task is and to whom. How can organizations do this? The director of the team examined in this study whose members had by far the highest perceived significance of the task suggested that you need to build a shared sense of cause within the team. Building this shared sense of cause will allow team members to feel their work is important. As a result, they may pull together to achieve greater success. If you can create a cause around something you usually get passion for it…. [You] can create this passion by gathering the stakeholders together… the business team participants all together in one place and allow them to see the direct impact of their project… One mechanism used by this director was to have the entire team meet at the site of a future customer. On site, the team worked with that customer to understand his/her needs as well as how he/she and future customers could be potentially impacted by the team’s product. The director also used a second mechanism for creating high significance. As illustrated in the quote below, this director made sure that the team members understood the careerenhancing opportunity that being part of the team gave them. [You] can also have passion when the management can demonstrate how the project will result in significant outcomes for the [team members] themselves because they will grow with this business opportunity. They will get to do things that they never thought they were going to do before. Equal responsibility for the outcome of the team’s efforts was found to be associated with satisfaction with the team. Therefore, shared responsibility for the outcome is an important task design variable for organizations to consider. In one of the teams studied, it was clearly not designed to have equal responsibility. In this team, there was a “leadership” sub-group and a “worker” sub-group. People in the leadership sub- 0-7695-2268-8/05/$20.00 (C) 2005 IEEE 6 Proceedings of the 38th Hawaii International Conference on System Sciences - 2005 group felt team spirit was good and communications were fine. People in the worker sub-group felt they were not involved with key decisions and did not feel they equally shared responsibility for the outcome of the project. They also had a significantly more negative view of the team’s spirit and communication processes. Therefore, organizations should be careful not to intentionally or unintentionally create sub-groups. In virtual teams, where part of the team may be collocated and part of the team remote, this can be particularly challenging. The supervisor of another team was aware of this potential problem. With 3 team members on-site and the remaining team members remotely located, he was very careful to treat all team members equally. He attempted to communicate, share information, and share responsibilities for the team’s task equally among the collocated as well as disperse members of the team. High autonomy was found to be positively associated with the output attitudes examined. This is consistent with research findings on effective collocated teams. According to Cohen and Bailey [5], the organization needs to give team members autonomy in their work. Worker autonomy has been shown to have clear benefits; it enhances worker attitudes, behaviours, and performance (whether measured objectively or rated subjectively by team members). Organizations should give team members the power to take action and make decisions about work and business performance. In the study, interpersonal skills were related to all of the output variables. This highlights the importance of training and developing strong interpersonal skills in virtual team members. Organizations can provide basic interpersonal skills to teams through training or through team member selection. Since team members are interdependent, one important interpersonal skill is the ability to communicate effectively. This skill can be especially important in virtual teams where effective communication is difficult. Time zones may be frequently crossed. Participants may have different national cultures which influence their natural communication patterns. Virtual team communications often rely heavily on asynchronous electronic media, which has limited feedback mechanisms. This limited feedback may lead to team members making false attributions about each other’s behavior. As Cramton [8] found in her research, in the absence of other information, people often attribute things like nonresponse to laziness or lack of interest, when in fact, it could be due to non-receipt or other very legitimate reasons. Thus, virtual team members need to agree on norms and expectations for communications so that false attributions, which could damage group cohesiveness and motivation, are not made. Skills have to be developed in this area as well. Some examples of how communication in virtual groups can be improved were suggested by participants. Team members themselves have to be responsive, quickly returning telephone calls and responding to emails, even if it is just to say, “I don’t have time right now but I’ll get back to you in two days with the answer”. Further, two virtual team managers suggested that the recipient actually confirm that the message had been received and ensure that the major points in the message were understood. Developing communication skills such as these could help to avoid misinterpreting interpersonal situations or behaviors. Another individual who had low motivation and satisfaction and rated the performance of their team as low commented on the importance of being able to communicate honestly and openly within the team. I think that it’s important when people feel they can really be honest about how they feel. And I don’t think we’re there… People will definitely hold back and they’ll do like a side complaint as opposed to you know just … this is how I feel and I mean not necessarily have a resolution or may have a resolution but I don’t … I think we’re not at the point where everyone can be completely honest. Team size and team turnover appeared to be positively associated with team performance, consistent with traditional team research findings [4]. All the negative comments from participants concerned having too small a team. Too small a team means the team does not have the resources necessary to effectively complete their tasks. Turnover of key team members can lead to inefficiencies from lack of norm development, increased efforts needed for orientation, and duplication of efforts. Organizations need to staff teams with an appropriate number of members and then keep the membership fairly stable. Two other sets of skills were identified as being positively associated with satisfaction with the team: technical skills and coordination abilities. Previous research supports the need for having adequate technical skills among team members to complete the team’s task and the importance of effectively coordinating efforts so time is not wasted and work is not duplicated [4]. To accomplish this, organizations can ensure that members on a team collectively have the skills required to complete the task. The organization can do this by carefully selecting team members whose skills complement each other, or provide training and development opportunities so that the needed skills can be acquired. Routine, frequent communications were mentioned by many of the team members as contributing to good coordination (see 0-7695-2268-8/05/$20.00 (C) 2005 IEEE 7 Proceedings of the 38th Hawaii International Conference on System Sciences - 2005 quote below). Good communications between members ensures that the team members know what each are doing and how their pieces of the project fit together, and helps to avoid duplication. I would think so [the team’s efforts were well coordinated] because we had weekly meetings so I would say it was very structured. We had weekly meetings and to follow up the weekly meetings were weekly minutes. You know and then the following week we followed up on any outstanding items. And then aside from that there were individual e-mails that might have gone, you know, between meetings, back and forth, so I would say it was well structured. In the teams studied, most routine meetings were carried out via teleconferencing. Another mechanism that was identified as aiding coordination was the use of Lotus Notes databases. Such technology can be used to store project information so team members and management can track the status of tasks, and to generally help teams manage their schedules. Project management tools such as Gantt charting software were also used by some of the teams. Team potency was found to be positively associated with all the output variables, implying that if an organization can increase team members’ beliefs in the abilities of the team, the team members will be more motivated and satisfied with being part of the team, and the team will be more effective. To increase team potency, organizations can select team members that have the required skills and abilities. However, this is not enough. Team members have to know about the skills and abilities that others bring to the team and develop a belief that the team will collectively succeed. Celebrating and recognizing achievements as they occur should also help build beliefs in abilities. We know from the extensive work on self-efficacy [1, 2] that previous successes enhance perceived efficacy and that self-efficacy is a powerful predictor of performance [17]. Generally it appears that if one does not believe that the team will succeed and operate well, one is less satisfied with being part of the team, and less motivated to contribute to the team. Team spirit was positively associated with all the output variables, suggesting the importance of this concept for organizations. Team spirit is demonstrated through working together with energy and caring about fellow team members [4]. Many of the team members felt that since face-to-face interaction is limited, creating strong team spirit in virtual teams can be difficult. For example, It is hard for the people who are far away to feel this [i.e. team spirit], especially if they are isolated and working on their own. In that case, they do not get exposed to the [company] culture and learn about it. This is also a problem for new people. It is hard to share culture and build team spirit, especially when remote from others. Yeah, I believe there was [a team spirit]... Like I said, it would have been better if we could all have gotten together for beers more often but, cheers, we have virtual beers. One team leader explained why team spirit was so strong in his virtual team: Yeah, I think so [a team spirit was present in the team] even though it was a virtual ... yeah it had a virtual spirit. But I mean I would get on the call and in the first five minutes, you know, talking about what's happening in everybody's personal lives… I mean it's ... we were interested in what everybody else was doing. Getting to know team members on a personal basis and demonstrating genuine interest in what they are doing should help build team spirit. Although this can be done effectively through face-to-face social settings, the quote above illustrates that it can also be accomplished at a distance. Setting aside time in teleconference calls for social time or a virtual coffee break can help people get to know each other better and enable them to better appreciate each other’s situation. In two of the teams, synchronous instant messaging was heavily used. Team members reported that many of the messages were of a social nature and that such messages helped them feel connected to the rest of the team. Future research efforts to help organizations understand how to establish team spirit in a virtual setting would be valuable. The discussion so far has focused on the relationships that were found between input variables and output variables. When there is ample evidence in previous team effectiveness research, why were no significant patterns found for many of the other input variables? A possible explanation is that the teams in this study did not exhibit enough variance in some of the input variables. The fact that many of these input variables had little variance and/or were often welldone by all teams is one limitation of this study. Therefore, we cannot yet conclude that these variables are not important inputs for effective virtual teams. Future research is needed to further understand these input variables and their significance for effective virtual teams. For example, future research could advance our understanding of degree of virtuality. In this study, the degree of virtuality did vary but no clear patterns were observed. This may indicate that degree of virtuality by itself is not a strong predictor of effectiveness, or is only important if other components are not strong (e.g. information technology support, coordination, communication, etc.). The validity of 0-7695-2268-8/05/$20.00 (C) 2005 IEEE 8 Proceedings of the 38th Hawaii International Conference on System Sciences - 2005 these conclusions can only be determined by future research into virtual team effectiveness. In conclusion, the geographic dispersion of team members in virtual teams makes it a significant challenge for organizations to develop and maintain effective virtual teams. Via case studies of six virtual teams, this paper has identified patterns and indications of what it takes to enhance a virtual team member’s satisfaction with being part of the team, their motivation with the project, and their team’s performance. Positive patterns were found between two or more of the indicators of effectiveness and task autonomy, interpersonal skills, team potency and team spirit. Managing these input variables well would be important for organizations with virtual teams, since doing so could positively affect the team members’ attitudes toward the work, leading to enhanced productivity and effective behaviour. It is hoped that this paper provides insights to organizations that are wrestling with the challenges of designing and maintain effective virtual teams, and identifies additional areas that researchers should focus on in the future. 6. References [1] Bandura, A. “Self-efficacy: toward a unifying theory of behavioral change”, Psychological Review, 1977, 84(2), pp. 191-215. [2] Bandura, A. “Self-efficacy mechanism in human agency”, American Psychologist, 1982, 37(2), pp. 122-147. [3] Bourdon, S. “Inter-coder reliability verification using QSR Nud*Ist”. Paper presented at Strategies in Qualitative Research: Issues and Results from Analysis Using QSR NVivo and QSR NUD*IST, September 30th. The Institute of Education, University of London, London, UK, 2000. [4] Cohen, S. G. “Designing effective self-managing work teams”, In M. M. Beyerlein, D. A. Johnson & S. T. Beyerlein (Eds.), Advances in interdisciplinary studies of work teams: Vol. 1. Theories of self-managed work teams. Greenwich, CT: JAI Press, 1994. [5] Cohen, S. G., and Bailey, D. E. “What makes teams work: Group effectiveness research from the shop floor to the executive suite”, Journal of Management, 1997, 23(3), pp. 239-290. [6] Cohen, S. G., Ledford, G. E., Jr., and Spreitzer, G. M. “A predictive model of self-managing work team effectiveness”, Human Relations, 1996, 49(5), pp. 643-676 [7] Cramton, C.D. and Webber, S.S. “Modeling the impact of geographic dispersion on work teams”, Working paper, George Mason University. 1999. [8] Cramton, C. D. “The mutual knowledge problem and its consequences for dispersed collaboration”, Organization Science, 2001, 12(3), pp. 346-371. [9] Gibson, B. G., Randel, A.E., and Earley, P.C. “Understanding group efficacy: An empirical test of multiple assessment methods”, Group & Organizational Management, 2000, 25(1), pp. 67-97. [10] Gladstein, D. L. “Groups in Context: A Model of Task Group Effectiveness”, Administrative Science Quarterly, 1984, 29, pp. 499-517. [11] Guzzo, R. A. and Shea, G. P. “Group performance and intergroup relations in organizations”, In M. D. Dunnette & L. M. Hough (Eds.), Handbook of industrial and organizational psychology: Vol. 3. Consulting Psychologists Press, Palo Alto, CA, 1992, pp. 269-313. [12] Guzzo, R. A., Yost, P.R., Campbell, R.J., and Shea, G. P. “Potency in groups: Articulating a construct”, British Journal of Social Psychology, 1993, 32, pp. 87-106. [13] Hackman, J. R. “The design of work teams”, In J.W. Lorsch (Ed.), Handbook of organizational behavior. Prentice-Hall, Englewood Cliffs, N. J., 1987, pp. 315-342. [14] Martins, L. L., Gilson, L. L., and Maynard, M. T. “Virtual Teams: What Do We Know and Where Do We Go From Here?” forthcoming in Journal of Management, 2004, 30(6). [15] Miles, M. B., and Huberman, A. M. Qualitative data analysis: An expanded sourcebook. SAGE Publications, Thousand Oaks, CA, 1994. [16] Shea, G. P. and Guzzo, R. A. “Groups as human resources”, In K. R. Rowland & G. R. Ferris (Eds.), Research in Personnel and Human Resources Management, 5, Greenwich, Ct.: JAI Press, 1987, pp. 323-356. [17] Stajkovic, A. D., and Luthans, F. “Self-efficacy and work-related performance: A meta-analysis”, Psychological Bulletin, 1998, 124(2), pp. 240-261. [18] Staples, D. S. and Cameron, A. F. “Creating Positive Attitudes in Virtual Team Members,” Virtual & Collaborative Teams: Process, Technologies, & Practice, S. Godar and P. Ferris (Eds.), Idea Group Publishing, 2004, pp. 76-98. [19] Yeatts, C., & Hyten, D. E. High-Performing SelfManaged Work Teams: A Comparison of Theory to Practice, Sage Publications, Thousand Oaks, CA. 1998. 0-7695-2268-8/05/$20.00 (C) 2005 IEEE 9 Proceedings of the 38th Hawaii International Conference on System Sciences - 2005 Appendix A: Construct Measurement Task Design Assessment • What are the variety of skill sets required to complete the task? How are these skills distributed among the team members? • On a scale of 1 – 7 point (1 = very little and 7 = very much) how would you answer the following question: How does the work, or project, affect the lives or well-being of others? • How much autonomy does the group have in determining the parameters of the task, the methods for achieving the task, or even the task itself? • What kind of feedback is provided to the group on their performance? Is feedback provided regularly, and is this feedback useful? • Is responsibility for the final outcome shared equally among all members? Team Composition Assessment • Are there adequate technical skills among the group members to complete the task? Do you feel that your individual technical skills are sufficient? • On a scale of 1 – 7 point (1 = very low, and 7 = very high), how would you rate the general level of interpersonal skills in your group? Why? • What level of relevant IT training and abilities do the team members have? Is it adequate for the existing IT tools? What level of IT training and experience do you as an individual have and is it adequate? • How many team members are there? Are there too few/too many team members to do a good job? • How long has the group been working together? Is there a high turnover in the group membership? How was the team first started / got to know each other? • How many members of the team are geographically dispersed? How dispersed is the team - # time zones spread out among members? How often do they meet face to face? Group/Team Potency [12] 1. My team has confidence in itself 2. My team believes it can become unusually good at producing high-quality work 3. My team expects to be known as high-performing 4. My team feels it can solve any problem it encounters 5. My team believes it can be very productive 6. My team can get a lot done when it works hard 7. No task is too tough for my team 8. My team expects to have a lot of influence around here Team Process Assessment • How would you characterize your team’s level of coordination? What is the level of duplication that occurs (or does any duplication occur)? • Is there a sense of team spirit in your group? Why ? • How comfortable are your team members with sharing important information within the team? How comfortable are your team members with taking advice from or deferring to someone in the team with greater knowledge or skill? • Has the team adopted or created any new innovations or inventions to improve your way of doing required tasks? Organizational Context Assessment • What is the reward system? How are rewards distributed? • How adequately is training available and supported? • Who has the information you need to do your job? How easy is it to get the information you need? • Does your geographic location hinder or increase your access to required resources? How difficult is it to acquire resources as the need arises, does your location make a difference? What resources (if any) do you feel are missing in your offsite work, compared to onsite work? • What kinds of IT tools / infrastructure are present? • Power/authority - What is the power structure in your team? What level of authority does your team have in making important decisions? Team Outcome Variables Team Performance • On a scale of 1 – 7 point (1 = very low, and 7 = very high), how would you rate your own team’s performance? Why? • Do you think your team is very effective (i.e. meeting objectives on time in an efficient and effective manner)? Why or why not? Motivation with the Task • On a scale of 1 – 7 point (1 = very low, and 7 = very high), how would you answer the following question: How would you characterize your level of motivation with your team’s current project? Why? Satisfaction with Being Part of the Team • On a scale of 1 – 7 point (1 = very low, and 7 = very high), how would you answer the following question: How would you describe your level of satisfaction with your team? Why? 0-7695-2268-8/05/$20.00 (C) 2005 IEEE 10