The construct validity of the research instrument was assessed
via confirmatory factor analysis (CFA). To perform a CFA, all of the
constructs and reflective indicators were depicted and composed
as a measurement model in which all constructs were allowed to
correlate with each other.
Generally speaking, the process of validation comprises the
steps as described below: the measurement model should demonstrate
robustness for the empirical data and meet the requirements
of the certain indexes. For example, chi-square normalized by
degrees of freedom (k/df), should be less than five (Bentler, 1989)
and it is 780/296 = 2.64 here; and comparative fit index (CFI)
should all exceed 0.9, and root mean square error (RMSEA) should
be less than 0.10 (Henry & Stone, 1994) and it was 0.92 and .065
here respectively. It suggests an adequate model fit for the empirical
data. In sum, the indices indicate that the model, which is a
representation of the HBM, can be accepted from an empirical
point of view and its robustness (for more details see: Hu and
Bentler (1999) and Kaiser and Scheuthle (2003)).
Furthermore, it is important to say that the v2-statistic generally
was significant in our models. Note that the v2-statistic is
affected by sample size, which is quite large in this study
(N = 389). Given the large sample size, however, significant v2
(Kaiser, 2006; Kaiser & Scheuthle, 2003) is consistent with previous
findings. In the next step, HBM was tested consecutively. The
results of SEM revealed that the (standardized) path coefficients
indicate the strengths of relationships between the variables