Properties of convolution same as LTI systems? I have attached a snapshot from "signal processing first "
Where author says that properties of LTI systems are same as properties of convolution as shown in attached snapshot 

Are these properties exactly same for both cases,convolution and LTI systems?and we don't need to apply any scaling etc?
The author simply means that the response of an LTI system $h[n]$ can be found by convolving the input sequence $x[n]$ with the $h[n]$. And in doing that all properties of convolution will hold true for LTI systems. Like, frequency response of an LTI system will simply become $X(e^{j\omega}).H(e^{j\omega})$, because convolution in time means product in $\omega$ domain.

You can look through all the properties on convolution operation at : ConvolutionProperties, and be sure that all of them will be held by an LTI System as well.

For example : Associativity : $$(x*h_1)*h_2 = x*(h_1*h_2)$$
In context with LTI systems, it means that if $x[n]$ is the input to two cascaded LTI systems $h_1[n]$ and $h_2[n]$, then we can actually, find out the equivalent LTI system by convolving the 2 cascaded systems as $(h_1*h_2)[n]$ and then find the output of this equivalent system by applying input $x[n]$ to it.

Similarly, you can see the relation between all of the convolution properties in context of an LTI system.