Quality, value, satisfaction, trust, a

ehavior courses participated as both respondents and recruiters. Each student was asked to
complete the survey and to recruit one other non-student to also complete the survey. Non-
student names and phone numbers were collected and randomly checked to ensure authenticity.
This process resulted in 308 total usable surveys (45% male, mean age 30); 241 completed their
last major purchase in a traditional store, while 67 completed their last major purchase online.
When answering the questions related to retail convenience, respondents were asked to
think about their most recent major purchase. This was done to increase the chance that
respondents would remember their purchase in as much detail as possible. Those respondents
who made their most recent major purchase in a traditional store were directed to the scale items
for in-store shopping, while those respondents who completed their most recent major purchase
online were directed to the “online shopping” section of the survey.
Statistical Technique
Several statistical techniques were used to analyze the data. In order to test Hypothesis 1,
statistics typically used in scale development were employed, including Cronbach’s alpha,
principal components analysis, and confirmatory factor analysis using LISREL 8.3 for Windows.
In order to test Hypotheses 2 through 4, analysis of variance was used to compare scale means of
access, search, and possession convenience for in-store and online shoppers.
Results
In order to test Hypothesis 1, statistical procedures commonly used in scale development
were employed. Reliabilities for each dimension of retail convenience were calculated using
Cronbach’s alpha. Principal components analysis with varimax rotation was also undertaken in
order to determine if five distinct dimensions were present for in-store shoppers, and four
distinct dimensions were present for online shoppers. A more stringent confirmatory factor
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