If we can solve these equations directly we will have a better understanding of the roles of the underlying characteristic equation.
By using the forward shift operator $\mathbb{E}$ such that $\mathbb{E} a_n=a_{n+1}, \mathbb{E}^2 a_n=a_{n+2}$, etc., a linear difference equation can then be written as $f(\mathbb{E})a_n=0$, where $f$ is a polynomial.
First order LDE: $(\mathbb{E} - r)a_n=0$. The solution is simply $a_n = r^n a_0.$
Second order LDE: $f(\mathbb{E})a_n=(\mathbb{E}-r)(\mathbb{E} - s)a_n=0$. From the first order case we have $$(\mathbb{E}-s)a_n = r^n (\mathbb{E}-s)a_0 \tag1$$ or equivalently
$$a_{n+1} - s a_n = r^n (a_1-s a_0)\tag 2$$
You can then solve this recursively (denote $C_1=a_1-sa_0$)
$$a_{n}=C_1 r^{n-1}+sa_{n-1} = C_1 r^{n-1} + s(C_1 r^{n-2}+sa_{n-2}) = C_1 (r^{n-1}+sr^{n-2}) +s^2 a_{n-2} = \cdots \tag{A}$$
And that's why we see the $r^n$ and $s^n$ terms in our final solution. This can be tedious but fortunately we have a shortcut method to solve it much more quickly:
By symmetry
$$(\mathbb{E}-r)a_n = s^n (\mathbb{E}-r)a_0 \tag3$$
Or equivalently
$$a_{n+1} - r a_n = s^n (a_1-ra_0) \tag4$$
Subtract (4) from (2) you get
$$a_n=\frac{a_1-s a_0}{r-s} r^n - \frac{a_1-r a_0}{r-s} s^n$$
You now see clearly that from first order to second order, a new geometric sequence component via the second root (assuming distinct roots) is "added" to the geometric sequence solution to the first order, regardless of the initial values. They always have the same form, the only differences are the coefficients which can be determined from the initial values.
We can apply this factoring technique repeatedly to a higher order LDE. There won't be a shortcut method like in the second order case but you can solve recursively as in $(A)$.
Another clean way to solve is via linear algebra. It's easy to show that big transition matrix has the same rank as the order of the LDE.