ABSTRACTThe analytic hierarchy process (AHP) is a decision analysis technique that uses judgments from a group of relevant decision makers and hierarchical decomposition to derive a set of ratio‐scaled utility measures for decision alternatives. This paper addresses a number of design issues involved in the implementation of AHP for large‐scale systems. Specifically, it describes the use of incomplete experimental designs for simplifying data‐collection tasks. The effects of reducing the size of the hierarchy through attribute deletion and the effects of including identical attributes on any given level also are eval