Algorithms – Combine Merge Sorting with Insert Sorting – Time Complexity

I learn algorithms from the CLRS book myself without help. There is an exercise that combines the merge sort {O (n log n)} with the insert sort {O ($ n ^ {2} $)}. If the subarrays in the merge sort reach a certain size "k", it is better to use the insert sort for these subarrays instead of the merge sort. The reason given is that the constant factors in insert sorting make it quick for small n. Can someone please explain that?

It asks us to show that (n / k) sublists with the length k can be sorted by insertion sorting in O (nk) worst case time. I found out from somewhere that the solution to this is O ($ nk ^ {2} / n $) = O (nk). How do we get this part O ($ nk ^ {2} / n $)?

Thanks a lot !