Operación de un CMS

According to the UTAUT model, attitude towards using technology, self-efficiency and anxiety are theorized not to be direct determinants of behavioural intention (Venkatesh et al., 2003). The authors found evidence that those variables have no significant effect on behavioural intention since the effect is captured by effort expectancy. The variables are included in the questionnaire to gather more information about the perception of the system by the user. Which can assist in explaining certain phenomena.

All three have low Cronbach’s Alpha scores which shows that there is little inter-correlation amongst the questions for each item. However, the results from the survey do provide some indications that the average participant is not really scared of losing data or other aspects of using the software. The average score on anxiety is 2.80, which indicates that on a scale of 1 to 7 the average subject slightly disagrees being anxious. When looking at the individual anxiety questions, AX1 to AX4 in Table 29 of Appendix C, it becomes clear that most people feel apprehensive about the system (AX1). Only AX1 has a mean that is almost neutral, with a score of 3.59. The remaining three questions have means of 2.32, 2.59 and 2.68 respectively for AX2, AX3 and AX4.

Even though feeling slightly apprehensive on average, with enough time or support, participants responded to be able to work with the system, hence the scores for self-efficiency are on average 4.83. In addition the test subjects have a positive attitude towards using the software, with a score of 5.39. Both the total values for self-efficiency and attitude towards using technology have a 99% probability (p < 0.01) of being above neutral, while the same applies for anxiety for being below neutral. The positive attitude confirms H3, with the 95% confidence interval being between 23.47 and 25.72, were neutral is represented by a value of 16. H3 even passes for p < 0.01 with confidence interval being between 23.09 and 26.12.

Besides the technology acceptance related constructs, the following three aspects were also measured: computer skills, expected future for virtual meetings in a 3D virtual environment and the participant’s background. The average participant self-assessed his or her computer skills with a value of 5.91 which is quite high on a scale of 1 to 7. The division of computer skills is displayed in Table 7, which shows that all, except one, rate their computer skills above average. Which makes proving H4 difficult. However, when looking at the overall experience of the user, as discussed earlier and summarized in Table 15, the users with high experience are less anxious about the system. Therefore an alternative hypothesis will be used:

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H4a: Users with high experience are less anxious about using the

system compared to users with low computer skills.

When performing a t-test to see if the null hypothesis, which suggests that there is no difference between the groups, can be rejected. The significance is 0.051 which is just above the 0.05 p-value. The significance should be below this value to pass the 95% confidence interval. Therefore with the current sample size the null hypothesis cannot be rejected with p < 0.05 and H4a has to be rejected as well.

Background N Mean Std. Deviation Performance Expectancy (PE) Professional 8 20.38 5.181

Student 11 16.82 3.544

Other 3 21.33 3.512

Effort Expectancy (EE) Professional 8 23.50 3.855

Student 11 21.64 4.411

Other 3 22.33 4.041

Attitude Towards Using Technology (AT)

Professional 8 24.63 1.847

Student 11 24.18 3.093

Other 3 26.00 2.000

Social Influence (SI) Professional 8 19.13 4.518

Student 11 19.64 2.976

Other 3 20.00 3.464

Facilitating Conditions (FC) Professional 8 21.13 4.051

Student 11 21.91 2.166

Other 3 21.33 5.033

Self-Efficiency (SE) Professional 8 22.13 4.016

Student 11 22.45 3.417

Other 3 19.33 9.609

Anxiety (AX) Professional 8 9.50 4.504

Student 11 11.82 3.417

Other 3 13.33 2.309

Behavioural Intentions (BI) Professional 8 15.13 4.486

Student 11 14.27 3.809

Other 3 13.67 6.110

Experience (EX) Professional 8 23.25 2.964

Student 11 19.27 4.149

Other 3 17.00 2.646

Age Professional 8 31.75 11.235

Student 11 24.55 2.806

Other 3 39.67 16.010

Voluntariness of use (VU) Professional 8 5.38 1.768

Student 11 5.64 1.567

Other 3 5.33 1.528

TABLE 17:CONSTRUCT VALUES BASED ON PARTICIPANT’S BACKGROUND.

The fifth hypothesis that suggests that users that are less anxious about the system have higher self- efficiency compared to anxious users. When dividing the group in two, one group having an anxious score of 16 or higher, being neutral or anxious, and the other group having a score below 16, being below neutral. This results in 5 participants in group one and 17 in group two. By performing a t-test to see if the null hypothesis can be rejected, the significance is 0.624. This means that the probability

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that both groups are different is relatively low, only 37.6%. Therefore the null hypothesis cannot be rejected and H5 cannot be accepted.

Another interesting result was already summarized in Table 8, showing the likeliness that there is a future for virtual meetings in a 3D virtual environment. The average result is a 6.23which indicates that, on a scale of 1 to 7, is very likely that there is future for virtual meetings in 3D environments. This confirms the expectations made earlier.

In Table 17 the results are grouped by the participant’s background. The participants were grouped in three categories: professional, student or other. Similar to the groups used by King and He (2006). One of the largest differences is visible in experience, the students and professionals that participated seem to have more experience on average with virtual meetings, content management systems and 3D environments. This can partly be explained by the difference in age, since the average age of the student and professional users is much lower than the other groups. The professional participants are the least anxious of the three groups, having the highest self-efficiency and effort expectancy averages. This seems to support the adjusted hypotheses H4 and H5, however both were not significant and thus rejected. Professional users seem to have the highest intention to use the system. Which indicates that the main target group accepts the system.