Quality, value, satisfaction, trust, a

examine the dimensionality of these constructs, principal components analysis with varimax
rotation was undertaken for each group separately. For in-store shoppers, five components with
eigenvalues greater than one were extracted from the data. Together, these five components explain
77.9% of the total variance. For online shoppers, four components with eigenvalues greater than
one were extracted; together, they explain 84.4% of the total variance. Thus, there is strong
evidence in support of Hypothesis 1; the dimensionality of retail convenience is different for the
two different types of shopping formats. Evidence of discriminant validity is provided by the fact
that these items did not want to load on other components with which they were not supposed to be
associated. Further, evidence of convergent validity is provided by the high loadings of each item
on their respective component.
A more rigorous examination of the validity of these scales was conducted with
confirmatory factor analysis using LISREL 8.3 for Windows. As can be seen in Tables 3 and 4, the
statistically significant λ x parameter estimates provide evidence of convergent validity.
Additionally, the majority of the squared multiple correlations (SMCs), defined as the percentage of
variance in each item that is explained by the latent construct of interest, are above 50%, indicating
that each item performed well in capturing its construct of interest.
Modification indices associated with λ x and Θ δ reveal some problems with discriminant
validity. Specifically, there were seven modification indices in the λ x matrix for in-store shoppers,
indicating that items search2, help3, possess1, and possess2 wanted to be associated with other
dimensions of convenience. Additionally, there were 13 modification indices in Θ δ that indicate
some error terms wanted to correlate. These changes were not incorporated in the model, as
theoretically it does not make sense to do so. These problematic modification indices explain the
poor overall fit: chi-square=498.08, 198 df, p=0.00; RMSEA=0.08; RMR=0.06; GFI=0.85.
Problematic modification indices also surfaced in the measurement model for online
shoppers. Three items (access2, possess2, and possess4) wanted to be associated with other
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