There is no dependency on dimensionality with regard to the order of transformations.
In 3D space, to obtain the camera view transform matrix, I believe it is scale * rotation * translation matrix...
Such statements are meaningless as long as
(1) one tells whether column vectors (like e.g. typically in OpenGL) or else row vectors (like e.g. typically in D3D) is used, and
(2) one tells what exactly the "camera view transform" means, and
(3) one tells what effect should be yielded in.
Usually, the camera transform is called what places the camera object into the world, i.e. the transformation from the camera local space into the global space. Also usually the view transform is the inverse of the camera transform, i.e. the transformation from the global space into the camera local (a.k.a. view) space.
With the above definition and the usage of column vectors, a camera transform is often build up as
C := T * R * S
what you will call
translation mul rotation mul scaling
but actually means
scaling on the mesh, rotating the scaled mesh, translating the rotated scaled mesh
The corresponding view transform is then
V := C-1 = S-1 * R-1 * T-1
where, if you stores the matrices as view matrices, you say
scaling mul rotation mul translation
Now, the same game with row vectors gives you
C := S * R * T
so that the order is reversed. This is true for all derived matrices, but the meaning is left as is! E.g. the above C actually still means
scaling on the mesh, rotating the scaled mesh, translating the rotated scaled mesh
This is the difference of column vs row vector math.
In the end you see that both orders are valid in both systems, depending of what you speak of. Furthermore, you can think of applications that are not as easy as the composite of 3 matrices above, giving perhaps other orders in both systems. Whenever you read about transformation matrices you must realize the convention used in the reading, or else you cannot exactly interpret what you read.
Hope that helps. Matrix math is a bit confusing if the caveats are not known.
