In this paper we describe a method that returns the order of decision
factors using ranking information, which can thus be interpreted as
an inverse approach of the well-known Analytic Hierarchy Process (AHP).
The adoption of the algorithm is conceivable in several fields, especially
in those that examine or employ human decision attitudes. The accuracy
of the method is investigated using both artificial and real data.
In the first case we could reproduce a set of artificially generated
importance orders of a fixed number of decision factors with a ninety
percent correspondence, while in the second we demonstrated how the
method works when people were asked to rank 100 different sports.
