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I have been working on antecedents of mobile shopping with UTAUT-2 model combined with the constructs of trust and perceived risk. I am using a sample of international students for my study. I wanted to check for impact of several exogenous variables like risk, trust, influence, structural assurance and facilitating conditions etc. along with age, gender variables on to the behavioral intention towards use of mobile shopping. All the reliability and construct validity measures are ok but I only introduced actual usage behavior in the end because there was only one DV and the degrees of freedom were zero and model fit values were also ambiguous. Below is the path diagram. and also the table of actual usage is below. for your kind reference. enter image description here

So now the R-squared correlation for behavioral intention is 0.78 and the regression effect from Behavioral_intention to actual usage is also good i.e. 0.32 but the real problem is that the R-squared correlation value for actual usage is only 0.10 which is a matter of concern for me. Let me tell you that since I have focused on expat students here in China and mostly they are using online mobile shopping apps. The actual usage measure adopted from Martins et al. (2014) a categorical value recording the actual usage of mobile shopping app from one-time usage in a year to several times usage a day. Only 13% of our users indicated use of mobile apps on a monthly basis whereas the others indicated usage as follows in the end. Is it due to the fact that since most of the users are overtly using the apps hence there is not much variation based on the underlying exogenous variables?

Kindly advise me on this as to what would be the reason for this much low value of R-squared of actual use of mobile app while the model is highly able to explain the intention to use mobile shopping.

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Behavioral_intention to actual usage is also good i.e. 0.32 but the real problem is that the R-squared correlation value for actual usage is only 0.10 which is a matter of concern for me.

$r$ (correlation) between behavioral intention and actual usage is $\approx 10$.

$R^{2}$ (coefficient of determination) for (presumably) linear regression of actual useage onto behavioral intention $= 0.32$

$R^{2} = r \times r$, and $r = \sqrt{R^{2}}$.

Kindly advise me on this as to what would be the reason for this much low value of R-squared of actual use of mobile app while the model is highly able to explain the intention to use mobile shopping.

So what you are seeing is that $0.32 \approx \sqrt{0.1}$

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  • $\begingroup$ Isn't this R-squared correlation taken as variance explained by this variable? I'm sorry if I couldn't explain my point here, actually, both of the R-squared values are close in practice but here it looks as if the model is able to explain lots of variance in the intention to use mobile shopping but the variance explained in actual use of mobile shopping is surprisingly very low i.e. 0.10 only. So I wonder what's wrong here and how to check for any corrections? $\endgroup$ – Muhammad Shahzad Hanif Sep 4 '18 at 20:24
  • $\begingroup$ @MuhammadShahzadHanif "R-squared" ($R^{2}$) is one thing. (Pearson's) Correlation ($r$) is another thing. There is no such thing as "R-squared correlation", you are merging two different concepts. Those two concepts have a relationship: $R^{2} = r \times r$, alternately $\sqrt{R^{2}} = r$. If $R^{2} \approx 0.1$, then there is no mistake if $r \approx 0.32$, since $\sqrt{0.1} \approx 0.32$. $\endgroup$ – Alexis Sep 5 '18 at 0:00

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