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									                           Multimedia and Virtual Teams:
                        Results of an Experimental Research
                     Yajiong Xue1, Chetan S. Sankar2, Victor W. A. Mbarika3


         With the rapid development and extensive application of information technologies, use of virtual
teams to encourage collaboration with students from other campuses is receiving increasing attention from
educators. Prior research has demonstrated that it is difficult for the virtual team to achieve the same
performance as the traditional face-to-face team. We wanted to study whether the use of a multimedia case
study into the teaming experience will narrow the gap between the performance of the virtual team and the
face-to-face team. An experiment was designed to compare the performance of eight virtual teams and eight
face-to-face teams of students from two universities. The teams were asked to solve a case study problem
and present the results using information technologies within a limited time. The performance of the teams
was measured during and at the end of the case study by means of students’ final grades, meeting records,
and an online survey involving five constructs. The results of the research led to rejecting the hypotheses
that the virtual team could achieve the same performance as the face-to-face team. The results indicated
that the virtual teams’ performance in terms of personal satisfaction, mission clarity, and group cohesion
were significantly lower than the face-to-face teams. There were no significant differences between the
performances of the two types of teams in terms of group behavior, skill development, time spent and final
grade perspectives. This paper interprets these results and discusses the findings.

                                             The Problem

         Sometimes people need to form teams and work together remotely to accomplish complicated tasks.
These teams with members from different geographic locations are called virtual teams (George, 1996). One
of the advantages of virtual teams is that it increases education and training opportunities for people of all
ages, lifestyles, capabilities, and financial situations (Belanger and Jordan, 2000). The other advantage is
that it enables people from different locations to join together to take courses and work together in solving

         Prior research provided substantial evidence that virtual teams communicate less efficiently than
face-to-face groups (Warkentin, Sayeed, and Hightwer, 1997). Virtual teams require modern networking
technologies to achieve high levels of mutual affinity and fast decision-making amongst their members (Bal
and Foster, 2000). However, researchers state that the current technologies do not allow virtual team
members exchange the same amount and richness of the information as face-to-face team members because
face-to-face meetings have broader bandwidth than most other media (Warkentin, Sayeed, and Hightwer,
1997; Chidambaram and Jones, 1993). This calls for educators to discover new approaches to improve the
virtual teams’ performance. We decided to use a multimedia case study as a new approach to impact the
performance of the teams.

1 PhD student in MITI, Department of Management, Auburn University
2 Thomas Walter Center Professor, Department of Management, Auburn University
3 Assistant Professor, Department of Information Systems and Decision Sciences, Louisiana State University

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Literature Review

       Previous studies have identified several factors that have impact on the performance of virtual
teams. The three most vital factors are task, technology, and time (3Ts).

        Carey and Kacmar (1997) did an experimental study to analyze the impact of communication mode
and task complexity on small group performance. They found that sensing/thinking subjects were more
satisfied with teleconferencing communication mode than intuitive/feeling subjects were. Hollingshead and
McGrath (1993) conducted a longitudinal study of computer-mediated groups versus face-to-face work
groups. The results revealed that there were no significant differences between these two groups on decision-
generating and decision-making tasks; however the groups working face-to-face performed significantly
better than the groups working on the computer for negotiation tasks. These findings indicated that the
nature of the tasks is closely associated with the virtual teams’ performance.

        Technology is another factor influencing the performance of the virtual team. According to the theory
of task-technology fit developed by Zigurs and Buckland (1998) in the group support system (GSS)
environment, achieving a fit between a group’s task and technology should be a principle for formulating an
effective group working environment. With a wide variety of electronic meeting systems and communication
media available today, the biggest potential challenge for a virtual team is to select the most appropriate
media/system combination (Chidambaram and Jones, 1993)

        There is evidence that teams evolve over time, and that the length of time the team members have
worked together can significantly influence group processes (Brannick and Prince, 1997). Time is an
essential factor that cannot be neglected in the virtual team studies. Therefore, one-shot study would be
inappropriate to investigate virtual teams’ performance. Chidambaram and Jones (1993) recommended that
longitudinal studies should be conducted to understand the performance of virtual teams so that the effect of
time can be incorporated into consideration.

Problem Statement

         The objective of this study was to examine if the formulation of virtual teams with a combination of
the task, technology, and time dimensions was able to enhance the performance of virtual teams to the level
of face-to-face teams.

Research Hypotheses

        A good combination of task, technology, and time would lead to virtual team of students performing
similar to the face-to-face team.


Design of Study

        The task used in this study was the analysis of a case study entitled “Operating Systems Choice for
Point-of-Sales (POS) Terminals at Chick-fil-A” (Raju and Sankar, 2001). The case study was provided in a

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multi-media format and requested students to help the company choose an operating system for their Point-
of-Sale (POS) terminals. The company had to move from its proprietary EPROM based system to a newer
system. Since Chick-fil-A owned over 700 corporate stores, this changeover had about a $3.29 million
investment impact stemming from the difference in prices between different implementations of the new
POS systems. The case study illustrated the technical, operational, and financial issues that need to be
resolved when working with state-of-the-art technologies and how the choice of an operating system impacts
the operations of the business.

       Multimedia Technologies
       Besides the traditional textbook, various multimedia technologies were utilized. The problem is
brought to life with use of images, photos, audios, and videos (Raju and Sankar, 2001).

       Communication Technologies
       In order to encourage students to use as many communication technologies as they can during their
meetings, a list of available communication technologies for them to use was provided at the beginning of the
study. The list included: email, telephone, the Internet, MSN Messager, AOL Instant Messager, AIM
Express Instant Message tool, Microsoft NetMeeting, and WebCT. A training program on using these
technologies was also provided to both classes. The training program emphasized on how to use Microsoft
NetMeeting (including video and audio conferencing, whiteboard, chat, Internet directory, file transfer, and
program sharing) and WebCT technology.

        To give students enough time to build trust among each other and make the study more realistic,
this study lasted three weeks. The first week of the study was designed for students to get to know each
other. In the second week, students started to do their assignment. In the third week, students summarized
their work and made power point slide presentations for their team projects.


        One class of senior MIS students from Auburn University (Auburn) and one class from Louisiana
State University (LSU) were selected as the subjects of this study. Each class had 32 students enrolled. The
authors randomly assigned the 64 students into eight face-to-face (FTF) teams and eight virtual teams with
four students in each team. Four face-to-face teams were composed of 16 students from Auburn and the
other four face-to-face teams were composed of 16 students from LSU. Each of the eight virtual teams
consisted of two students from Auburn and two from LSU. The eight virtual teams worked on the team
project together but from different geographic locations. The set up is shown in Figure 1.

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       Figure 1. Subject Assignment

                  Auburn University                         LSU
                       (N=32)                              (N=32)

             4                                   ..                     4

             4                                                          4

             4                                                          4

             4                                                          4

           FTF Teams                                                FTF Teams

                                      Virtual Teams

Instrument Development

        Based on the 18 short scales of Campbell-Hallam Team Development Survey (TDS) (Hallam and
Campbell, 1997), team performance in this study was measured by 7 scales. The seven scales included
mission clarity, group cohesion, group behavior, skill development, personal satisfaction, time spent, and
final grades. These were measured by an online self-assessment survey. It was completed by every team
member after the case study. The questions on the survey were evaluated using a 5-point scale format with 1
representing strongly disagree, 2 representing disagree, 3 representing neutral, 4 representing agree, and 5
representing strongly agree.

        A team-meeting tracking form was used during this study to keep track of the time spent by each
team. Team members were asked to fill out the team-meeting tracking form every time they finished a
meeting. In addition, the two faculty members gave each team a final grade for the Chick-fil-A case study
after students’ final presentation. The grades were based on assessment criteria with which both professors


Data Analysis

        The study lasted for three weeks. In the first week, students in face-to-face teams met together and
students in virtual teams changed their email addresses and telephone numbers through email or telephone.
During the second week, students started to work on the problems. All the teams reported in their team-
meeting tracking forms that they had used some communication technologies in the list provided to them.
Interestingly, despite our advocacy of Microsoft NetMeeting, only one virtual team reported that they used
the whiteboard, file transfer, and program sharing functions of this software. Other teams reported that
their teammates at the remote site felt unsafe to reveal their computers’ IP addresses. Therefore, they did

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not use Microsoft NetMeeting. In the third week, students gathered together and made power point slides
for the project presentations.

        One student of a virtual team and two students of two different face-to-face teams dropped the class
during the three weeks and they were excluded from the study. Since previous research has shown that
there is no significant difference in behavior between three and four-person groups (Chidambaram and
Jones, 1993), the team composition in this study was still considered as intact.

        Analysis of Measurement Reliability

        Reliability is one of the major concerns of measurement before analyzing the data and drawing
conclusions from the results (Kerlinger, 1986). The reliability of the questionnaire was evaluated using
Cronbach’s alpha. As shown in table 1, the Cronbach’s alpha coefficient of each construct is above 0.70,
indicating the data were stable, dependable, and predictable.

        Table 1. Analysis of Measurement Reliability: Cronbach’s Alphas

Items                                                                           Cronbach’s 
Mission Clarity (MC)                                                            =0.92
MC1. Face-to-face team/virtual team members can easily understand the
mission of the team.
MC2. It is easy for face-to-face team/virtual team members to understand
the purpose of each meeting.
Group Cohesion (FC)                                                             =0.74
GC1. I felt my self was really a part of our face-to-face team/ virtual team.
GC2. If I had a change to do the same work again in a face-to-face
team/virtual team, I would rather stay in the same face-to-face team/ virtual
GC3. If I had a chance to do the same work again, I would rather join a
virtual team/ face-to-face team
Group Behavior (GB)                                                             =0.87
GB1. Team members were open and frank in expressing their ideas and
GB2. Team members were committed to the goals and objectives of the
GB3. Team members recognized and respected individual differences and
contributions during the case study.
Skill Development (SD)                                                          =0.89
SD1. I improved my technical ability through this experiment.
SD2. I improved my teamwork ability through this experiment.
SD3. I improved my decision-making ability through this experiment.
Personal Satisfaction (PS)                                                      =0.92
PS1. Overall, I was personally satisfied with the face-to-face team/virtual
team decision-making process.
PS2. Overall, the quality of my face-to-face/virtual team’s interaction was

        One-way ANOVA test was used in analyzing the results of the online survey (see table 2). The
results showed that there were significant differences between the face-to-face team and the virtual team on

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teams’ mission clarity, group cohesion, and personal satisfaction. The mean value of mission clarity for face-
to-face teams is 4.02 while the mean value for virtual teams is 2.76. These two means differed significantly
with the p-value less than .05 (+.000). The mean of group cohesion for face-to-face teams is 3.87 while the
mean for virtual team is 2.80. These two values differed significantly with the p-value less than .05 (+.000).
The mean value of personal satisfaction for face-to-face team is 4.17 while the mean value for virtual team is
3.15. These two were also significantly different with the p-value less than .05 (.001). As regards the other
two factors, i.e., group behavior and skill development, there were no significant differences between the
virtual teams and the face to face teams.

        Table 2. One-way ANOVA results

Items                       Face-to-face     team    Virtual team mean         F- value      Sig.
                            mean      and      SD    and SD (N=31)
Mission Clarity                         4.02(.81)                2.76(1.13)          24.71          .000
MC1                                      4.00(.87)               2.77(1.18)          21.31          .000
MC2                                      4.03(.89)               2.74(1.18)          23.11          .000
Group Cohesion (GC3                     3.87(.92)                2.80(1.09)          17.05          .000
GC1                                    4.07(1.11)                3.13(1.45)           7.96          .007
GC2                                    3.80(1.03)                3.03(1.47)           5.54          .022
GC3                                    2.27(1.31)                3.77(1.31)          20.18          .000
Group Behavior                          4.03(.86)                 3.92(.76)            .27            .60
GB1                                      4.00(.98)                 3.94(.81)           .08            .78
GB2                                      4.13(.97)                 4.03(.87)           .18            .67
GB3                                      3.97(.96)                 3.81(.87)           .46            .50
Skill Development                      3.84(1.05)                3.67(1.25)            .64            .43
SD1                                      3.77(.94)               3.58(1.12)            .50            .49
SD2                                      3.87(.82)                 3.65(.91)           .99            .32
SD3                                      3.90(.92)               3.77(1.02)            .25            .62
Personal satisfaction                  4.17(1.05)                3.15(1.25)          11.84          .001
PS1                                    4.13(1.07)                3.42(1.23)           5.80          .019
PS2                                    4.20(1.06)                3.87(1.41)          17.22          .000

        The face-to-face team and the virtual team’s total meeting time spent on the case study was
calculated after collecting all the team meeting tracking forms from all 16 teams. The result of One-way
ANOVA indicated no significant difference between meeting times of the two types of teams.

        Table 3. Time Spent Data Analysis

                        Total time spent (in         F - value                 Sig.
                        minutes) mean and SD
Face-to-face    teams   291.75 (125.11)              .51                       .49
Virtual teams (N=8)     341.25 (150.26)

         The 16 teams’ final grades did not show significant difference between face-to-face teams and virtual
teams. An explanation for the fact that the mean value of the virtual teams’ final grades is a little higher
than the face-to-face teams’ was that the two professors in this study admitted that they considered the
difficulty of virtual teams when they gave teams grades.

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       Table 4. Final Grade Data Analysis

                        Final Grade (out of     F - value               Sig.
Face-to-face   teams    9.01 (.31)              4.36                    .056
Virtual teams (N=8)     9.29 (.22)

Limitations and Implications

         There are some limitations for this study. First, the deadlines of the case study of the two
universities were different. The Auburn’s deadline was 3 days earlier than LSU’s deadline. This difference
possibly caused some disharmony among the virtual members from different schools. Some virtual team
students in Auburn complained that their teammates in LSU were not as motivated as they were before the
Auburn due date. On the other side, some LSU virtual team students thought their teammates from Auburn
were too pushy. Second, there were only eight face-to-face teams and eight virtual teams used in this study.
It was possible that the differences could not be detected only because of the low statistical power to reject
the null hypotheses. Future research needs to use more teams to address this concern. Third, this study was
a pilot study that used only one case study. Future research needs to be conducted based on more than one
case study. Finally, the seven factors did not cover all aspects of team performance. More factors can be
investigated in the future to gain deeper insights into the performance of virtual teams.

Interpretation and Conclusions

         The above results suggested that virtual teams had lower mission clarity, group cohesion, and
personal satisfaction than the face-to-face teams, whereas there were no significant differences between
these teams regarding the other four aspects: group behavior, skill development, time spent, and final grade.
The seven scales we used in this study were measuring seven different aspects of team performance. These
scales were treated equally and no weight was assigned to them. Although the authors tried to find a good
combination of task, technology, and time in the study, the results showed that the integration of the
multimedia technology in the case study did not make virtual teams achieve the same performance as the
face-to-face teams. Our findings confirmed previous research contending that it is very difficult for virtual
teams to achieve the same performance as face to face teams. This study extended research on virtual teams
by incorporating complicated task and multimedia technology into our research domain.

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     Group Performance and Member Satisfaction, Computers in Human Behavior, Vol. 13, No. 1, pp. 23-49

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Yajiong Xue

Yajiong Xue is a Ph.D. student of MIS in the Department of Management at the College of Business, Auburn
University. She holds a B.S. in International Business from China Pharmaceutical University and a Master
degree in MIS from Auburn University. She has worked for Pharmacia & Upjohn and Kirsch Pharma GmbH
for several years. She has presented in national conferences and contributed papers to international journals
and professional conferences. Her current research interests include the innovations in education, business
integration of information technology, strategic management of information technology, mobile commerce,
and health care information technology.

Chetan S. Sankar

Chetan S. Sankar is currently the Thomas Walter Professor of Management at Auburn University's College
of Business. He received his Ph.D. from the Wharton School, University of Pennsylvania and has worked at
Temple University and at AT&T Bell Laboratories. He is a Co-Principal Investigator of four National
Science Foundation grants worth more than a million dollars. The objective of these grants is to develop
exceptional instructional materials that bring real-world issues into classrooms and to improve the higher-
level cognitive skills of students. These instructional materials have been published and made available as
nine textbooks that include multimedia CD-ROM supplements. The case studies and supplements bring
alive the issues faced by Southern Company, Powertel, Chick-fil-A, AUCNET USA, and other companies into
the classrooms. In addition to his current research and teaching interests, Dr. Sankar has published more
than 100 papers in journals, book chapters, and conference proceedings. He has won many awards for
research and teaching from the Society for Information Management, NEEDS and John Wiley and Sons,
Decision Sciences Institute, American Society for Engineering Education - Southeastern Section, American
Society for Mechanical Engineering, Auburn University, and the Project Management Institute. In order to
promote the research interests of other academicians who want to publish high-quality case studies and
papers that integrate real-world issues with theories in science, mathematics, engineering, and technology
(SMET) fields, he co-edits the Journal of SMET Education: Innovations and Research. Further information
about Dr. Sankar’s research and teaching accomplishments could be obtained from the web site:

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Victor W. A. Mbarika

Dr. Victor W. Mbarika is Assistant Professor of Information Systems and Decision Sciences at the E. J.
Ourso College of Business Administration, Department of Information Systems & Decision Sciences,
Louisiana State University. He holds a B.S. in Management Information Systems from the United States
International University Nairobi/San Diego, CA, a M.S. in Management Information Systems from the
University of Illinois at Chicago, and a Ph.D. in Management Information Systems from Auburn University.
His research in Multimedia Learning and his research in Telecommunications Diffusion in Developing
Countries have been published in several academic journals. He has also presented his research at several
national and international conferences on Information Systems. He holds several teaching and academic
excellence awards from several institutions of higher learning.

Dr. Mbarika is a KPMG scholar, a Southern Regional Education Board (SREB) scholar, and a Research
Fellow for the Laboratory for Innovative Technology and Engineering Education (LITEE), Auburn

Dr. Mbarika is Founder and President of Cameroon Computer and Network Center (CCNC); a member of
the Association of Information Systems (AIS), the Information Resources Management Association (IRMA),
and the Institute of Electrical and Electronics Engineers (IEEE).

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