Abstract
Statistical and decision-making techniques for solving prioritization problems are described. These approaches include the analytic hierarchy process (AHP) of the multi-attribute decision-making and its extension to the statistical modeling and testing, scaling techniques of priority estimation, maximum difference models, identification of key drivers in regression, and other methods. The described techniques have been widely applied and proved to be helpful for identification and ordering the most important items in solving various marketing research and decision-making problems.
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