*4.1. Sample*

The sample of the quantitative study was composed of 172 individuals, representing di fferent job positions in di fferent sectors of activity, to achieve a good representation of the active population at the national level. According to the sociodemographic data collected (Table 1), 108 (62.8%) are male, and 64 (37.2%) are female. A large part of the respondents is in the 41 to 54-year-old age group (54.07%), and most individuals hold a bachelor's degree (43.6%). The segmen<sup>t</sup> that stands out the most is the one having over 10 years' seniority in the organization, where 35.47% of the respondents are found, followed by the range between 2 and 5 years of seniority (27.9 %). Most of the respondents have an open-ended contract (77.33%).


The data collection was carried out between the months of March and May 2020. After the application of the data collection instruments, the responses of the participants were collected via the online questionnaire, and statistical analysis were subsequently prepared. Regarding the data analysis procedures, SPSS (version 25.0) was used for the statistical analysis. We performed the descriptive analyses regarding the characterization of the sample, the analyses of the Kaiser-Meyer-Olkin test (KMO) and Bartlett's sphericity test for the instruments and also for the correlations between variables. In order to determine the final constitution of the variables, Cronbach's alpha analysis was carried out in a first phase, which allows the exclusion of minor items.

To test the effect of sociodemographic variables on AOC, Mann–Whitney U non-parametric tests (bilateral significance) and the Wilcoxon test were performed to test the effect of gender on variables, and for the remaining sociodemographic variables, the Kruskal–Wallis non-parametric H test was performed. The Mann–Whitney U test is a non-parametric test used to compare two independent samples (in this case being male/female). The Kruskal–Wallis non-parametric H test extends the Mann–Whitney U test when there are more than two groups. It is used to compare two or more independent samples of the same or different sizes. The hypotheses tests were also carried out through Spearman's rank correlation coefficient, used for assessing the significance of relations between variables using statistics. This correlation coefficient is a statistical measure of the strength of the relationship between the relative movements of two variables. The values range between −1.0 and 1.0. A correlation of −1.0 shows a perfect negative correlation, while a correlation of 1.0 shows a perfect positive correlation. A correlation of 0.0 shows no linear relationship between the movement of the two variables.

#### *4.2. Reliability and Internal Consistency*

The reliability and internal consistency of the questions was measured using Cronbach's alpha coefficient (α), with a value of α = 0.951 for the EB scale and α = 0.883 for the AOC scale (Tables 2 and 3).

**Table 2.** Reliability and internal consistency for employer branding (EB) and affective organizational commitment (AOC) scales.



**Table 3.** Reliability and internal consistency for EB dimensions.

According to Hair et al. [56], Cronbach's α values obtained for the dimensions are greater than 0.70, which confirms a good reliability of the QEB (questionnaire of employer branding) scale globally and for each of the dimensions. As AOC is a unidimensional variable, a reliability and internal consistency table for AOC dimensions was not presented.
