RESPONSIBLE ENTREPRENEURSHIP VISION DEVELOPMENT AND ETHICS

Service quality and brand personality in hotel and hospitality the case of Romanian hotels 179
consistently load on the same factor. The way to test reliability in an EFA is to compute Cronbach’s
alpha for each factor. Cronbach’s alpha should be above 0.7. Each factor should aim
to have at least 3 variables.
Thus, we calculate the Cronbach Alpha index for each of the four factors. For the first
factor the Cronbach Alpha is 0.965, which is greater than 0.7, a very good result and each
factor has at least three variables. Cronbach Alphas are greater than the baseline value of 0.8,
we can say that the exploratory factor analysis is reliable and we can trust the obtained value
and we can go on to the confirmatory analysis.
Confirmatory factor analysis
Confirmatory factor analysis (CFA) is a multivariate statistical procedure that has the scope
of checking how and in what terms the constructs are represented by variables. We conduct
CFA in the next step of the analysis because in comparison to exploratory factor analysis (EFA)
it allows specifying the number of factors and it also let us decide which measured variable
is related to which latent variable. In EFA all measured variables are related to every latent
variable, because EFA explores the data and provides information about the number of factors
that are represented by the data. We choose CFA to study the relationship between observed
variables and continuous latent variables because it is a useful tool, given the fact that it confirms
or rejects the measurement theory or the causal relationship that explains the comprehensiveness
of a phenomenon.
The confirmatory factor analysis depicts four factors. The latent variables are the variables
that are inferred, not directly observed, from other variables that are observed.
From the obtained output, all hypotheses are confirmed with a Sig. smaller than 0.01, showing
a level of significance of 99%, which reveals a good model fit. Questions 2 and 11 to 21
directly affect service quality, questions 1 and 3 to 9 directly affect employee quality, questions
23, and 25 to 27 and 33 and 34 directly affect brand personality and questions 36 and
41 and 43 directly affect brand value and brand loyalty.
Structural equation modeling
Structural equation modeling (SEM) is a comprehensive and complex statistical procedure
that is used to represent, estimate, and test a theoretical complex structure of relationships
between variables, measured variables and latent constructs.
We base our study on the following hypotheses:
H5: Service quality does positively and significantly influence brand value and brand loyalty.
H6: Employee quality does positively and significantly influence brand value and brand
loyalty.
H7: Brand personality does positively and significantly influence brand value and brand
loyalty.
According to the values obtained in the Regression Weights table, we observe that service
quality (Factor 1) influences factor 4 (brand value and brand loyalty) with a significance
level of 99%, employee quality (Factor 2) does not influence factor 4 because the Sig. value
is 0.204, and lastly, Factor 3 (brand personality) influences Factor 4 with a probability of 0.034,
a significance level of 96.6%.