## 3 Research Design
### Q-Methodology Approach  
In a Q-Methodology study, respondents are typically presented with a sample of statements about a given topic, known as the \"Q-set\". The \"P-set\" of respondents is asked to rate the assertions from their point of view, using a quasi-normal distribution (Figure 4). The respondents disclose their subjective point of view [85] or personal perspective [86] by \"Q-ranking\" the assertions. The Q-Methodology traditionally intends to give a picture of the perspectives that exist (the variety of perspectives) among the population, rather than analyzing the level of support for those perspectives among the population (the balance of perspectives). It also relies on purposive sampling and smaller sample sizes. The fact that there is a person who is assumed to have a different point of view is enough reason to include him or her in the sample. Correlation between personal perspectives then implies the existence of  
Figure 4: Sample Q-grid. Figure 3: Conceptual framework. similar viewpoints or segments of subjectivity [87]. Q-factor analysis provides information on similarities and differences in the viewpoint on a specific subject by correlating people. For this research, only internal stakeholder perspectives (a short characterization of the internal stakeholders can be found in Table 5) were collected to identify the applicable success criteria for R&D Centers, which in turn may apply for the CFAA. To define the applicable success criteria, the Q-Methodology procedure with the subsequent steps were followed:  
* Reviewing the existing success criteria of the CFAA. * Defining new criteria, based on the literature. * Performing a trial run of the Q-sort. * Revising statements for the final Q-sort with the CFAA's internal stakeholders. * Perform Q-sorts with the selected stakeholders. * Assessing gathered data by using the software from [PERSON] [88]. * Interpreting results (factors) from the software. The first step of the defined procedure was to evaluate existing criteria of success of the project in terms of relevancy to the current research and revising unclear statements. To assess the criteria developed by the previous research at the CFAA, brainstorming was used as a method for eliminating, extending, or changing the unclear criteria. The case study was conducted by members of the CFAA's Project Management Office. As mentioned previously, the original version of Q-Methodology consists of 48 statements [78]. In this case, the grid was reduced to 25 cells to reflect the current number of statements. Further statements could have been identified; however, most of the participants were overwhelmed by many options, since this type of experiment had never been conducted before at the CFAA. Subsequently, 25 statements were generated and a table with the range from \(-4\) to \(+4\) was formed. The meaning of the ranking was slightly adjusted so that \(+4\) represents \"the most important criteria\" and \(-4\) represents \"the least important criteria\" in terms of their own perspective as an employee or internal stakeholder of the CFAA. As it is crucial that the distribution reflexes their own view and not the organizational viewpoint, this issue was pointed out to the participants. To ensure that the defined Q-set is understandable, and the formulations are unambiguous, a trial version of the Q-Methodology survey was conducted. In the trial evaluation of the new criteria, six people from different positions in the CFAA participated. Before the trial run was conducted, the general principle of Q-Methodology was explained and a short introduction of the performed research was provided. The trial run was conducted in groups of two, to enable discussions, since people often struggle to express their thoughts loudly. Since the first interviews were conducted on a trial basis and the aim was to understand whether all statements are clear and easy to understand, it was not necessary to apply the procedure individually.