Gender Differences In College Students’ Online Shopping: Utilitarian And Hedonic Motivation Approaches

2040 words - 9 pages

5. Methodology
5.1 Research Participants and Data Collection
A convenient sampling was done among the university students in Guangdong province. The students are form UIC, Beijing Normal University (Zhuhai) and Beijing Institute of Technology (Zhuhai), these three multi-culture universities are expected to ensure our sample from all around the country. Owning to survey is going to define the shopping behavior based on gender; the number of data will be controlled which the scale of male and female will be half and half. We use a questionnaire to collect data from 300 students, a total 205 completed questionnaires was considered for final analysis. The grade of college and region represented ...view middle of the document...

5.3 Statistical Analyses
The use of multi-sample structural equation modeling is appropriate as the theory of TAM suggests that a moderating relationship among predictors may vary by specific population subgroups such as gender, age and ethnicity. (Timothy, 2010). In other word, female and male will be tested respectively, then, these measurements invariance of two sub-groups will be compared. The coefficient between different paths will be tested by AMOS system for female and male apart. By comparing the coefficients it would get the result of our survey.
According to the definitions and measurements of the variables mentioned above, we use path analysis to construct the basic model, which is:
yi= βi xi + Ɛi
In order to test the H1, we should apply the formula to show relationship between the perceived usefulness and the attitude in this study. The model is established as follow: Ai= βi Ui + Ɛi, where
Ai = Attitude of online shopping
Ui = Utilitarian Motivation
Ɛi = Error
βi = The relationship between PU and Attitude which is the path coefficient
(i is for female or male students, and they will be tested respectively)
As the result, there are two path coefficients will be given in this formula, for female or male students respectively, we will compare the difference between this two path coefficients to find out whether there is a moderating effect on gender.
And the next step, we prepare to test H2 which the relationship between the hedonic motivation and the attitude about online shopping. The model as follow:
Ai= βi Hi + Ɛi, where
Ai = Attitude of online shopping
Hi = Hedonic value of online shopping
Ɛi = Error
βi = The relationship between hedonic motivation and Attitude
(i is for female or male students, and they will be tested respectively)
In the same way, we will test the gender difference of H3a and H3b in this model by comparing different path coefficients. The models as follow:
H3a: Ui= βi PEOUi + Ɛi
H3b: Ai= βi PEOUi + Ɛi, where
Ui = Utilitarian Motivation
Ai = Attitude of online shopping
PEOU i = Perceived ease of use of online shopping
Ɛi = Error
βi = The relationship between tow variables
(i is for female or male students, and they will be tested respectively)

6. Results
6.1 Multiple group invariance test
The multiple group measurement model invariance test as a reliable method for determining measurement equivalence across groups (Myers et al. 2000). The measurement invariance across gender groups was verified using multiple group invariance tests. The results of the x2 difference test of measurement weights against an unconstrained model (x2=44.396, df=25, at p-value=0.102) indicated no significant difference in measurement items among the models. This indicated equivalent measure across the gender groups in testing the study hypotheses. Thus, measurement invariance exists across gender groups and this enabled the present study to proceed to the structural model evaluation.

6.2 Hypotheses testing and structural model...

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