If your PDE and your discretization are linear, then your numerical method can be written as
$$U_{n+1} = A U_n$$
where $A$ is a square matrix. One way to investigate stability is to look at some induced matrix norm of $A$: if it is larger than 1, the discretization is unstable. This is completely general and is probably what you are looking for. Below I explain that von Neumann analysis is just a special case of this general approach.
If $A$ is a normal matrix (i.e., if $AA^T = A^T A$), then to show stability it is sufficient to check that the eigenvalues of $A$ are not larger than 1 in modulus. That is because for normal matrices, the induced 2-norm is equal to the modulus of the largest eigenvalue.
If the problem has periodic boundary conditions and a standard finite difference discretization is used, then $A$ will be a circulant matrix. Circulant matrices are normal, and the eigenvectors of circulant matrices are just discrete Fourier modes. This makes it easy to compute their eigenvalues, and von Neumann analysis is simply a way of determining those eigenvalues.