The findings were examined using factor analysis to
determine the key SEA policy drivers for SWM policy
planning in Malaysia and analyzed using general linear
model (GLM) multivariate analysis to determine if there was
a statistically significant difference between age, gender and
sector groups. Consequently, a SEA policy structural equa-
tion modelling (SEM) was developed using Analysis of
Moment Structures (AMOS) on the SEA policy model and
extracted for latent factors of policy drivers (policy awareness, environmental attitude, perceived benefit, perceived barriers, perceived enablers need and SEA integration
behaviour). The SEA policy model was empirically tested
using the maximum likelihood estimation (MLE) method
which enables the simultaneous examining of interrelated
dependence relationships among the measured variablesand the latent driver constructs as well as between the latent driver constructs. The measurement model was assessed for
reliability and validity using the Cronbach’s alpha coefficients
and the composite reliability coefficients while a
confirmatory factor analysis was conducted to verify the
validity of the latent variables. The structural model was
examined for fit and the proposed hypotheses tested for
statistical significance in the predicted direction of the
structural paths. Finally the SEA policy model was assessed
for the total and indirect effects of each predictor drivers
based the SEA policy model’s theoretical framework. The
individual indicator driver constructs used in the questionnaire is provided in Section 4 (Table 2).