  We provide an axiomatic characterization of the Logarithmic Least Squares
Method (sometimes called row geometric mean), used for deriving a preference
vector from a pairwise comparison matrix. This procedure is shown to be the
only one satisfying two properties, correctness in the consistent case, which
requires the reproduction of the inducing vector for any consistent matrix, and
invariance to a specific transformation on a triad, that is, the weight vector
is not influenced by an arbitrary multiplication of matrix elements along a
3-cycle by a positive scalar.
