Factors Influencing Success of Virtual Groups - Essay Example

Factors Influencing Success of Virtual Groups The increased use of computer technology in management hasprompted managers in most organizations to embrace the use of virtual teams that are self-managed. However, it’s necessary to tackle the issue of trait-configuration and composition of these virtual teams in order to improve their efficiency. The performance of a virtual team is significantly influenced by traits such as perceived different problem solving demands, within-the-team conscientiousness, and within-the-team extroversion. This research was conducted to show how negative or positive these traits affect performance of virtual teams in an organization. The descriptive statistics provided by the authors on their research findings forms a good basis for understanding the role played by these traits in influencing performance and efficiency of a virtual team. In the course of reading this article, I will apply myself to the issues brought about in the question paper. The key research questions in the study include: i) How will within-virtual-team extroversion influence performance in virtual teams?? ii) What is the impact of within-virtual-team conscientiousness variance on group performance? iii) How does the interplay between within-virtual-team consciousness variance and within-virtual-team extroversion dissension influence group performance? iv) How does the variation of within-virtual-team perceived problem-solving requirements affect performance in virtual teams? Key findings Consciousness variance affects virtual team performance performance in a negatively for extroversion incongruity values below 0.76/0.46=1.52. Since 77% of the sample that forms the majority falls is in this range, then it is evident that conscientiousness variance impacts negatively on performance of virtual teams (Turel & Zhang, 2010). This supports the second hypothesis which states that within-virtual-team conscientiousness variance will have a negative influence on performance of virtual team. Secondly, within-virtual-team extroversion variance does not have a positive effect on virtual team’s accomplishments since this measure did not receive any backing in the presence of a term of interaction. Thirdly, a variation in terms of extroversion helps reduce the negative impact of conscientiousness deviation on virtual teams’ performance to a great extent. Therefore, the interplay between within-virtual-team conscientiousness variations and within-virtual-team extroversion variations will have a positive impact on virtual the performance of virtual teams. Lastly, variations on perceived problem solving methods within the team impacts negatively on performance of that particular team; hence members of a team who have similar levels of perceived of perceived requirements for problem solving make a positive contribution to group performance (Turel & Zhang, 2010). Therefore, team performance is negatively influenced by perceptions on requirements for solving problems within that particular team. Measures used In this study, nominal scale was used as seen in the selection of those interviewed, who were aged between ages 19 and 42, with their mean age being 24. The sample was further classified into two; males and females with the value of the range between the persons interviewed being 30 persons. Data classification was also based on years of study, whereby half of the sample was juniors, a third was sophomores and the remaining one sixth was seniors, and percentages were used to show the mode in that juniors made the most appearances in the distribution. The yardsticks for extroversion and conscientiousness were taken away from Mowen, and it was a requirement for the interviewees to affirm the extent to which they endorsed extroversion statements concerning themselves. The level of this measure is ordinal and its mean was 1.05 with a standard deviation of 0.94, implying that the data is closely clustered around the mean, and that the data collected was very reliable. On the other hand, they were asked to express the extent to which they agreed or disagreed with such statements their personal organization, precision and efficiency for the measure of conscientiousness, whose level was ordinal with the mean of 0.96 and the standard deviation of 1.10 (Turel & Zhang, 2010). From the figures stated above, it is clear that the data collected was widely spread and therefore less reliable as evidenced by a very high standard deviation. The third measure of supposed problem solving was based on the arguments of Morgeson and Humphrey, where the subjects were asked to express how much they agreed or disagreed with a set of statements concerning the project in order to capture their perceptions on problem solving requirements (Turel & Zhang, 2010). This involved solving problems that have no answers that are easily perceived, demanded that the individual be creative, dealing with problems that are unfamiliar, and required that solutions for the problems be unique. This measure again, is in an ordinal level, whose mean was 1.01 and whose standard deviation was 0.93. These figures show that the collected data was reliable and less widely spread, hence clustered around the mean. In all cases, the collected data on all measures was ordinal since the students were ranked as beginners, sophomores and seniors. The authors used percentages to express the mode (77% of the sample interviewed showed that conscientiousness influences performance negatively for sociability variance values below 0.70/0.46 only) since the average is not used as the measure of central tendency for this kind of data. Also, the purpose of the data collected was to be used for comparison purposes hence the data was on an ordinal scale. The data collected was meant to measure team members’ cognitive abilities which qualify it to be treated as interval or ratio scales. This explains why the authors have given the means for the data which are otherwise not allowed if the data was classified under the ordinal level. Depending on one’s perspective, the measures used can be put into interval, ratio, nominal and ordinal levels. The reason as to why the standard performance has a mean of zero and a standard deviation of one due to the fact that the distribution of data in this kind of performance is uniform. If one plots a histogram representing the data on the standard performance, the resultant graph would be symmetrical and the corresponding normal curve would be bell-shaped with no skewedness. This is important when it comes to normalization of scores in a test so as to achieve a normal curve. The provided descriptive statistics were appropriate for the types of data due to the following reasons: one, they clearly bring out the sample characteristics as shown in the means and standard deviations. The data being ordinal by nature, the provided descriptive statistics clearly bring out the relationships between the three variables discussed and performance of groups. The primary objective of the research was to show the roles played by variances in conscientiousness, extroversion and problem solving in improving or worsening team performance. The provided descriptive statistics have clearly brought out these correlations which have helped support or reject the formulated hypotheses. The key issue authors faced in their analysis was inadequate demonstrable support that had been given to trait to the effects of configuration, more so to the joint outcome of various person-team fit views in such settings as online association. It is an issue since there is an increased use of computer technology in most management systems. In order to bridge this gap, the authors used self-reported data for purposes of prediction and standardized grades assigned to teams as variables for outcomes. In addition to bridging this gap, the method used by the authors makes several contributions theoretically, methodologically and in practice. Managers are required to assess the issues of organization of imitation teams and the characteristics of individuals who make up the group before assigning self-managed teams in their organizations. The number of individuals in a team does not matter, but the composition of that particular team since a team with fewer similar minded individuals can be more efficient than a team with many individual with divergent opinions on problem solving approaches. This implies that the within-team characteristic and differences in terms of task conception play an important role in team performance as opposed to the number of individuals making up the team. Online and offline teams need to be better utilized by modern organizations hence the need for further research on this topic to help these organizations understand and improve these virtual teams. Descriptive statistics provide managers with an insight on performances, which in turn forms the basis for inferences and decision making in the firm. Reference Turel, O., & Zhang, J. (2010). Does virtual team composition matter? Trait and problem-solving configuration effects on team performance. Behaviour & Information Technology, 29 (14), 363-375. Read More