Exploratory factor analysis explores the patterns of
relationships among a number of variables i.e. the latent
structure of a set of variables (Hair et al., 1998). As the
variables load highly on a factor, they become descriptors of
the underlying dimension.EFA using principal components
method was used to assess dimensions from the instrument
items. The items are removed one at a time by the criteria-the
Kaiser-Meyer-Olkin(KMO) value should be higher than
0.60.Bartlett’s test of sphericity is a measure of multivariate
normality and tests whether the correlation matrix is an
identity matrix indicating that the factor model is
inappropriate. Both the tests indicated that the data are
appropriate for factor analysis.