When you say "the person has to taken another decision between different alternatives," I get the impression that the set of possible choices depends on the last choice made. Because of this the model I would suggest is the Markov Model.
In its simplest form, the Markov Model involves a random walk on a graph. At each node on the graph there is a multinomial distribution which captures the probability of transitioning to other nodes (states) in the graph. Because each transition is governed by a lone multinomial distribution, this makes the process "memoryless," in the sense that your probability of going to a given state depends only on your current state.
If you would like to make things a bit more exciting there is no reason that at each node you could not have a multinomial distribution conditioned on some features. For instance maybe one demographic is more likely to transition $A \rightarrow B$ than others.