## 5 Evaluation
### Quantitative User Experience Survey  
The UX was measured before the developed prototype was submitted to the qualitative evaluation. First, this allowed us to ensure that the prototype would be tested again by third parties. Second, measuring the prototype's UX also reduced or even prevented possible biases due to user interaction in the qualitative analysis. Managers and experts were invited to evaluate the prototype. To ensure that the developed prototype also represented the expected customer journey, and that the experts were not biased by any problems with the user experience of the software, the UX was measured using quantitative methods. The user experience questionnaire (UEQ) developed by [PERSON] et al. [52] was used. This approach was based on a questionnaire with 26 questions and 6 scales. Note that questionnaires are a common and effective approach used for evaluating a product and its features [53].  
Twenty people took part in evaluating the application presented in this article. The authors of the UEQ explicitly state that it makes no sense to determine a single value representing the 26 medians (e.g., a median of the medians), since this value could not be interpreted in a meaningful manner. Instead, each question corresponded to one of the six scales. Thus, a mean of medians was computed for each scale. According to the authors of the UEQ evaluation tool [52], the individual means can be evaluated in the following manner: The value scale ranges from \(-3\) (extremely bad) to \(+3\) (extremely good) but, realistically, the value of each mean will be somewhere between \(-2\) and \(+2\). This difference in values is because the medians from which the means are computed are based on various responses from various people with diverse opinions and answer tendencies.  
Consequently, good results such as \(+1.5\) on a scale of \(-3\) to \(+3\) appear worse than they are. The results of the evaluation are shown in Figure 7.  
The mean value for attractiveness was 0.86, meaning that the evaluation was positive. However, there was still some room for improvement. With a value of 0.4, perspicuity was perceived as neutral. On the other hand, the results for efficiency paint a completely different picture. Here, the mean was \(-0.28\). Even if the evaluation here did not fall below \(-0.8\) and, therefore, did not fail, improvements needed to be made. One reason for this might be the hash value creation. Using our prototype VM setup, the hash creation took about two minutes. The creation of hash values needed to be improved by having a faster VM setup during the focus group discussion. With a result of 1.24, the application's dependability was good--there was no need for improvement here for the focus group discussion. The result for stimulation was 0.7; thus, it was neutral and fine for demonstration purposes. Novelty achieved a result of 1.27, which was also extremely good. This high novelty value is probably since users did not yet know of any other application that would have enabled them to configure cloud applications via dApps. All in all, quantitative methods were used to show that the UX of the developed prototype was within the expected customer journey, and that the prototype could be presented to the focus group without any significant UX bias.  
Figure 7: User experience evaluation results.